P < 0.05) relative abundances of Prevotella, Butyrivibrio, Pseudobutyrivibrio, Methanobrevibacter.gottschalkii, Neocallimastix, Anoplodinium–Diplodinium, and Polyplastron, and lower relative abundance of Methanosphaera (P = 0.042) were detected in the rumen of S kids when compared to those in G kids. The expression of genes encoding TLRs, IL1α, IL1β and TICAM2 was down-regulated (P < 0.01), while expression of genes encoding tight junction proteins was up-regulated (P < 0.05) in the ruminal mucosa of S kids when compared to that in G kids. Moreover, irrespective of feeding type, relative abundances of ruminal Prevotella, Fibrobacter, Ruminococcus, Butyrivibrio, Methanobrevibacter, Neocallimastix, and Entodinium increased with age. The expression of most genes encoding TLRs and cytokines increased (P < 0.05) from day 0 to 7, while expression of genes encoding tight junction proteins declined with age (P < 0.05). This study revealed that the composition of each microbial domain changed as animals grew, and these changes might be associated with variations in host mucosal innate immune function. Moreover, supplementing goat kids with concentrate could modulate ruminal microbial composition, enhance barrier function and decrease local inflammation. The findings provide useful information in interpreting microbiota and host interactions, and developing nutritional strategies to improve the productivity and health of rumen during early life.Gastrointestinal microbiota may play an important role in regulating host mucosal innate immune function. This study was conducted to test the hypothesis that age  and feeding type [Supplemental feeding (S) vs. Grazing (G)] could alter ruminal microbial diversity and maturation of host mucosal innate immune system in goat kids. MiSeq sequencing was applied to investigate ruminal microbial composition and diversity, and RT-PCR was used to test expression of immune-related genes in ruminal mucosa. Results showed that higher ( Ruminants have a remarkable ability to convert human-indigestible plant biomass into human-digestible food products through rumen microbial fermentation . BacteriThe rumen fermentation products are mainly absorbed by the ruminal epithelial wall, and utilized by the host . In addiBacteroides fragilis are capable of activating and modulating immune responses in the host (TLRs) on the host mucosa can recognize conserved microbial domains, and trigger host innate immune responses -domain containing adaptors.To address this knowledge gap, we hypothesized that age  and feeding type  could modulate ruminal microbiota, and further manipulate host mucosal innate immune function. To test this hypothesis, we applied a combination of MiSeq sequencing and relative RT-PCR analysis to investigate microbial diversity, as well as expression of genes encoding All management and experimental procedures were approved by the Animal Care Committee, Institute of Subtropical Agriculture, the Chinese Academy of Sciences, Changsha, China.Thirty-two Liuyang black goat kids were separated from their dams after birth, and maintained within individual pens for the duration of the study. From birth to day 20, kids consumed goat milk and 4 kids were slaughtered at day 0 and 7 (non-rumination phase), respectively. The remaining 24 kids were randomly allocated to two groups based on different feeding types, supplemental feeding (S) and grazing (G). Between day 20 and 40, kids in S group consumed milk, forage plus concentrate, while kids in G group consumed milk and forage. The animals were weaned at day 40. From day 40 to 70, S kids were provided with concentrate and forage, while G kids grazed 8 h on pasture daily, and returned to pens overnight without receiving any extra feed. In both groups, four kids were slaughtered at each of the following ages: day 28, 42 (transition phase) and day 70 (rumination phase). All kids had free access to water. Detailed feeding management, and ingredients of concentrate and forage have been described in our previous parallel study .After the kids were slaughtered, ruminal digesta samples were collected from five locations  within the rumen (∼10 g each). The samples were composited, and aliquots were stored at -80°C for subsequent DNA extraction and sequencing analysis. Ruminal mucosa samples were collected from the same sites where digesta samples were collected, and rinsed three times with sterile phosphate buffered saline . Afterward, the mucosa samples were separated from the underlying muscular layer, cut into 3 mm × 3 mm fragments, composited, frozen in liquid nitrogen and stored at -80°C for later molecular analysis.® SV Gel and PCR Clean-Up System . Barcoded amplicons were mixed at equal molar rations, and submitted for 300 bp pair-end sequencing on an Illumina MiSeq PE300 instrument .Genomic DNA was extracted using the QIAamp DNA Stool Mini kit  and quantified using NanoDrop ND1000 . Conventional PCR was conducted to amplify bacterial V2–V3 and archaeal V6–V8 regions of the 16S rRNA genes, as well as fungal V3–V5 and protozoal V4–V5 regions of the 18S rRNA genes using primers detailed in Supplementary Table Raw data were filtered through Quantitative Insight into Microbial Ecology (QIIME)  and MothFor bacteria and archaea, the assembled sequences were assigned to operational taxonomic units (OTUs) at a 97% identity threshold using UPARSE . ChimeriAlpha diversity was examined using the alpha rarefaction pipeline of QIIME. Principle coordinate analysis (PCoA) was performed using unweighted UniFrac distance (jackknifed beta diversity from resampling 100 times at a depth of 75% of least number of sequences). Transformation-based principal component analysis (tb-PCA) was used to ordinate the samples based on OTU abundance data using the Hellinger distance , and onlTLRs, inflammatory cytokines, toll-IL-1 receptor (TIR)-domain containing adaptors, and tight junction proteins (TJs), with GADPH and β-actin as the housekeeping genes. The primers are listed in Supplementary Table Total RNA was extracted from mucosa samples (200 mg) using TRIzol reagent . The RNA integrity was evaluated using 1% agarose gel electrophoresis, and its quantity was measured using ND1000 spectrophotometer . The RNA was reversely transcribed using the First Strand cDNA Synthesis Kit , and the cDNA samples were stored at -20°C until use. The RT-PCR analysis was used to evaluate expression of genes encoding The effect of feeding type was examined from day 28 to 70. Data were analyzed using the MIXED procedures of SAS 8.2 . Feeding type, age, and feeding type × age interaction were regarded as fixed effects, animal nested within feeding type × age was regarded as the random effect, and each individual animal was the experimental unit. The following model was used:ijk = dependent variable, μ = overall mean, Ai = fixed effect of age, Fj = fixed effect of feeding type, Anik = random effect of animal nested within feeding type × age, and eijk = the random residual error.where YThe effect of age on ruminal microbial diversity and expression of genes involved in host mucosal innate immune function was evaluated from day 0 to 70. The MIXED procedure of SAS and Tukey’s test to compare least squares means were used, with age as the fixed effect, animal within age as random effect, and individual animal as the experimental unit. The following model was used:ij = dependent variable, μ = overall mean, Ai = fixed effect of age, Anij = random effect of animal within age, and eij = the random residual error. Orthogonal contrasts were performed to test linear and quadratic effects of age. If feeding type × age interaction was not significant within day 28 to 70, effect of age was assessed using combined data of both groups; otherwise, they were presented separately. All data were presented as least squares means, and significance was declared with P < 0.05.where YP < 0.05 were defined as correlated with each other and plotted using corrplot package in the R studio.The PROC CORR procedure of SAS was used to examine the Spearman’s rank correlations between ruminal microbial abundance and expression of mucosal innate immune function related genes. Only those correlation coefficients above 0.50, and PRJNA362795.Sequencing data in this study were deposited in the NCBI Sequence Read Archive (SRA) under accession numbers Supplementary Figure S1 and Table P < 0.05) in G kids compared to that in S kids. Alpha diversity indices  of ruminal bacteria and archaea in both groups increased with age (P < 0.01). For G kids, alpha diversity indices of ruminal fungi increased (P < 0.01), while those indices of ruminal protozoa decreased quadratically (P < 0.05) with age. PCoA analysis revealed that microbial communities could be clearly discriminated by both age and feeding type . The tb-PCA results revealed the top 10 OTUs within each microbial domain contributing to separation at different ages and for feeding types . Details of these are presented in Supplementary Text As reflected by rarefaction curve, sequencing depth was adequate to cover the community of each microbial domain, with Good’s coverage ranged from 0.980 to 0.999 . Relative abundances of Prevotella, Asteroleplasma, Coprococcus were greater (P < 0.05), while relative abundances of Butyrivibrio and Pseudobutyrivibrio were lower (P = 0.011) in the rumen of G kids compared to those in S kids. In both groups, Arcobacter (30.1%), Escherichia (13.3%), Porphyromonas (5.7%) and Fusobacterium (2.1%) were predominant ruminal genera at day 0, whist their relative abundances declined to minimal values (<0.2%) afterward. Conversely, Prevotella relative abundance increased drastically (P < 0.01) with age, being the most dominant genus after day 28 (>20%), while Bacteroides relative abundance was high (12.1%) at only day 7. Moreover, relative abundances of ruminal BF311, CF231, Butyrivibrio, Pseudobutyrivibrio, and Fibrobacter in both groups increased quadratically (P < 0.05) with age. After day 28, relative abundances of ruminal Asteroleplasma and Anaeroplasma ranged from 0.3 to 1.2% in G kids, while their ruminal relative abundances were low (<0.2%) in S kids. Relative abundances of ruminal Akkermansia, Corprococcus, Ruminococcus, Selenomonas, Succiniclasticum and Treponema ranged from 0.1 to 3.6% in both groups. And relative abundances of Enterococcus and Lactobacillus were low (<1.0%) in the rumen of both groups.A total of 20 phyla and 48 genera were identified in all samples, with 23 bacterial genera each accounting for >0.5% of all sequences. A great proportion of sequences (31.2–69.2%) remained unclassified at the genus level , while relative abundances of genus Methanosphaera, as well as Group 11 and 12 within the Methanomassilliicoccales order were lower (P < 0.05) in the rumen of S kids compared to those in G kids . Within the Methanobrevibacter genus, relative abundances of Mbb. gottschalkii (16.1–66.7%) and Mbb. ruminantium (2.9–9.7%) clades increased drastically from day 28, constituting the top two abundant clades. The highest relative abundance of Mbb.acididurans in the rumen of S and G kids was 15.9% (day 70) and 3.7% (day 70), respectively. Relative abundances of Methanimicrococcus and Methanosphaera genera were low (<2.0%) in the rumen of both kids, while Methanomicrobium genus was only detected in the rumen of S kids at day 28 (6.4%). Furthermore, a significant proportion of Methanomassilliicoccales (from 12.1 to 34.8%) was found in the rumen of both groups.Archaea were not detectable at day 0, and began to be detected at day 7. The relative abundance of Ascomycota and Neocallimastigomycota, and 103 fungal genera were identified, with 16 fungal genera each accounting for >0.5% of all sequences . The relative abundance of Neocallimastix was greater (P < 0.001), while relative abundances of Microcyclosporella, Knufia, Parastagonospora and Uwebraunia were lower (P < 0.05) in the rumen of S kids compared to those in G kids. Ruminal Boeremia (25.6%), Neurospora (11.3%), Arthrinium (7.6%), Aspergillus (4.5%), Purpureocillium (4.3%) were the top five abundant genera at day 0, while their relative abundances declined significantly (P < 0.01) afterward. The highest relative abundance of Candida in the rumen was 56.4% (day 7). The relative abundances of Knufia, Microcyclospora, Microcyclosporella, Parastagonospora, Penidiella, Phoma and Uwebaunia in the rumen of S kids were low (<2%) at all ages, while their relative abundances in the rumen of G kids increased with age (P < 0.05). Relative abundances of ruminal Neocallimastix and Piromyces in S kids increased quadratically with age (P < 0.05), peaking at 94.2% (day 28) and 61.3% (day 42), respectively, while their ruminal relative abundances in G kids increased linearly with age (P < 0.05), peaking at 7.1% (day 70) and 14.3% (day 70), respectively.Two fungal phyla, Figure 3D). The relative abundances of Anoplodinium–Diplodinium and Polyplastron were greater (P < 0.05), while Polyplastron relative abundance was lower (P < 0.001) in the rumen of S kids compared to those in G kids. Entodinium was the most abundant genera (39.9–96.8%) in the rumen, with its relative abundance declined linearly (P = 0.001) in S kids, while increased linearly (P = 0.002) in G kids from day 28 to 70. Relative abundances of Anoplodinium–Diplodinium and Polyplastron were high (8.2–87.4%) in the rumen of S kids, but low (<3.0%) in the rumen of G kids. In contrast, the relative abundances of ruminal Epidinium and Eremoplstron-Diploplastron were low (<1.0%) in S kids, but high in G kids (7.3–32.4%).Protozoa began to colonize after day 28, with >99% sequences classified into six genera (TLRs (1–10) was down-regulated in the ruminal mucosa of S kids when compared to that in G kids. For S kids, mRNA abundance of TLRs1, 2, 4, 7, and 10 increased slightly (P < 0.05) from day 0 to 28, and then decreased afterward . The mRNA abundance of other TLRs increased during the first week (P < 0.05), and declined afterward. Conversely, for G kids, expression of TLRs increased from day 0 to 28 (P < 0.01), remaining relatively stable afterward.The expression of genes encoding IL1α and IL1β was up-regulated (P < 0.01), while expression of IL10 and TNFα was down-regulated (P < 0.01) in the ruminal mucosa of G kids when compared to those in S kids . The mRNA abundance of IL1α, IL1β and IL6 in the ruminal mucosa of S kids increased from day 0 to 28, declined afterward, while their expression in the ruminal mucosa of G kids increased (P < 0.05) from day 0 to d 70. In both groups, mRNA abundance of IL10, IL18 and TNFα in the ruminal mucosa declined with age (P < 0.05).When genes involved in cytokine production were compared, the expression of TIR domain-containing adaptors, MYD88 expression was age- and feeding type-independent . The expression of TICAM2 (P = 0.003) was up-regulated in the ruminal mucosa of G kids when compared to that in S kids. Age exerted a quadratic effect (P = 0.006) on TICAM1 mRNA abundance in the ruminal mucosa of S kids. TICAM2 mRNA abundance in the ruminal mucosa of S kids increased during the first month and declined afterward, whist its value in G kids increased (P = 0.043) from day 0 to 70.For genes encoding TJs), the expression of Occludin, Claudin1 and Claudin4 was elevated (P < 0.05) in the ruminal mucosa of S kids when compared to those in G kids . Furthermore, expression of TJs declined (P < 0.05) from day 0 to 70 in the ruminal mucosa of both groups.For genes encoding tight junction proteins  relative abundances of Anaeroplasma, Knufia, Piromyces, Uwebraunia, and Entodinium, while negatively correlated with (R < -0.50) relative abundances of Mbb. gottschalkii and Anoplodinium–Diplodinium. TLR2 mRNA abundance was negatively correlated with (R = -0.52) Anoplodinium–Diplodinium relative abundance, TLR4 mRNA abundance was negatively correlated with (R = -0.50) Mbb. gottschalkii relative abundance, while TLR3 mRNA abundance was positively correlated with (R > 0.50) relative abundances of Knufia and Uwebraunia. TLR6 mRNA abundance was positively correlated with (R > 0.50) relative abundances of Anaeroplasma, Kufia, Neocallimastix, and Uwebraunia). TLR8 mRNA abundance was positively correlated with (R > 0.50) relative abundances of Kufia, Neocallimastix, and Uwebraunia, while negatively correlated with (R = -0.61) Mbb. gottschalkii relative abundance. TLR9 mRNA abundance was positively correlated with (R > 0.50) relative abundances of Fibrobacter, Anaeroplasma, Kufia, Neocallimastix, Uwebraunia, and Epidinium. TLR10 mRNA abundance was positively correlated with (R = 0.51) Neocallimastix relative abundance, while negatively correlated with (R < -0.50) relative abundances of Anoplodinium–Diplodinium and Polyplastron. The mRNA abundance of IL1α and IL1β was negatively correlated with (R < -0.50) relative abundances of Mbb. gottschalkii, Anoplodinium–Diplodinium and Polyplastron. IL6 mRNA abundance was positively correlated with (R = 0.60) Mmc.Group10 relative abundance, while IL18 mRNA abundance was negatively correlated with (R = -0.59) Epidinium relative abundance. The mRNA abundance of IL10 and TNFα was positively correlated with (R > 0.50) Bacteroides relative abundance, but negatively correlated with (R < -0.50) relative abundances of Bacteroides, Prevotella, Coprococcus, Fibrobacter, Anaeroplama, Methanosphaera, Phoma, Piromyces, and Uwebraunia. The mRNA abundance of Occludin, Claudin1 and Claudin4 was negatively correlated with (R < -0.50) relative abundances of most microbes. TICAM1 mRNA abundance was positively correlated with (R = 0.63) Mmc.Group10 relative abundance, while TICAM2 mRNA abundance was negatively correlated with (R < -0.50) relative abundances of Mbb. gottschalkii and Anoplodinium–Diplodinium.As presented in TLRs and TJ proteins suggest that shifts in microbiota may influence the development of ruminal mucosal innate immune function. Historically, rumen epithelial wall has been considered “immune intact” for its tolerance in highly dynamic and abundant microbiota. However, recent studies have highlighted its innate immune function for the consistently detectable expression of genes encoding TLRs and TJ proteins in dairy and beef cattle (TLRs) similar to the identified mechanism in the intestinal tissues of monogastric animals.The goats underwent a drastic change in nutrient supply from a high-fat milk diet during non-rumination stage to a forage and concentrate based diet during rumination stage . Therefof cattle , and thef cattle . It is kf cattle . This suTLRs was detected in the rumen of kids during the first week of life. It has been reported that the elevated expression of TLRs is associated with cytokine production . In intensive farming, supplementation of concentrate to young ruminants at a relative early age is a common practice which is considered to enhance the development of rumen  and epithelium (Butyrivibrio and Campylobacter)   increaseobacter) . It is wobacter) . Secondlesponses .TLR signaling and pro-inflammatory cytokines revealed a potential to resist local inflammation in the ruminal mucosa of S kids  and the effect of feeding type intervention . During the first week of life, milk nutrients facilitate colonization of mucin-degraders and fungi (Candida), which activate TLR signaling and provoke potential local inflammation. The starch and fiber alters microbial composition and diversity in ruminal digesta and mucosa, leading to enhanced SCFAs, especially butyrate production. These partly contribute to decreased inflammation by lower TLR signaling, and enhanced barrier function through stable TJs signaling, suggesting a mechanism to minimize superfluous inflammatory responses to commensal microbiota in S kids . Furthermore, supplementing kids with concentrate alters ruminal microbial composition, diversity and products, giving rise to lower inflammation and enhanced barrier function . Although the role of commensal microbiota on host mucosal immune function in the rumen is far from clear, our results provide some cues on the communication between ruminal microbiota and ruminal mucosal immune function that can be manipulated by dietary changes and developmental ages.To our knowledge, limited studies research on microbiota and host innate immune function cross-talk in the rumen, and how such interaction can be impacted by dietary interventions. Based on the findings from current study, we proposed a working model for interactions between ruminal microbiota and mucosal innate immune function during animal development in S kids  and expression of genes involved in ruminal mucosal innate immune function was age-related in both supplemental feeding and grazing goat kids. Concentrate supplementation during the early stages of life had the potential to modulate ruminal microbial composition, enhance barrier function and decrease local inflammation. Our results provide a model for integrating information on ruminal microbial diversity and function with measures of host mucosal immunity in the maturing ruminants. Future studies are warranted to investigate the actual contribution of specific microbial species in modulating host mucosal innate immune maturation.JJ and ZT designed the research; JJ and CZ conducted the research; ST and MW were involved in the animal experiments; JJ, LG, and CM performed the statistical analysis and contributed to the interpretation of results. JJ and LG wrote the draft of the manuscript. All authors read, approved the final manuscript, and have no competing interests.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The objective of our study was to clinically and etiologically investigate acute outbreaks of respiratory disease in Finland. Our study also aimed to evaluate the clinical use of various methods in diagnosing respiratory infections under field conditions and to describe the antimicrobial resistance profile of the main bacterial pathogen(s) found during the study.Actinobacillus pleuropneumoniae (APP), swine influenza virus (SIV), porcine reproductive and respiratory syndrome virus (PRRSV), porcine respiratory coronavirus (PRCV) and Mycoplasma hyopneumoniae antibodies. Polymerase chain reaction (PCR) was used to investigate the presence of porcine circovirus type 2 (PCV2) in serum and SIV in the nasal and lung samples. Pathology and bacteriology, including antimicrobial resistance determination, were performed on lung samples obtained from the field necropsies.A total of 20 case herds having finishing pigs showing acute respiratory symptoms and eight control herds showing no clinical signs suggesting of respiratory problems were enrolled in the study. Researchers visited each herd twice, examining and bleeding 20 pigs per herd. In addition, nasal swab samples were taken from 20 pigs and three pigs per case herd were necropsied during the first visit. Serology was used to detect Ascaris suum were the main causes of respiratory outbreaks in 14 and three herds respectively, while the clinical signs in three other herds had a miscellaneous etiology. SIV, APP and PCV2 caused concurrent infections in certain herds but they were detected serologically or with PCR also in control herds, suggesting possible subclinical infections. APP was isolated from 16 (80%) case herds. Marked resistance was observed against tetracycline for APP, some resistance was detected against trimethoprim/sulfamethoxazole, ampicillin and penicillin, and no resistance against florfenicol, enrofloxacin, tulathromycin or tiamulin was found. Serology, even from paired serum samples, gave inconclusive results for acute APP infection diagnosis.According to the pathology and bacteriology of the lung samples, APP and A. suum, PCV2 and certain opportunistic bacteria were also detected during the outbreaks; however, viral pathogens appeared less important than bacteria. Necropsies supplemented with microbiology were the most efficient diagnostic methods in characterizing the studied outbreaks.APP was the most common cause for acute respiratory outbreaks in our study. SIV,  Actinobacillus pleuropneumoniae (APP), Mycoplasma hyopneumoniae (MHyo), Mycoplasma hyorhinis, Haemophilus parasuis (H.parasuis), Pasteurella multocida and Streptococcus suis [Porcine respiratory disease complex (PRDC) is a syndrome caused by mixed viral and bacterial pathogens together with environmental, managerial and genetic factors . A combicus suis –6. Oftencus suis , 6, 7. Mcus suis . The patcus suis .Pathogens involved in PRDC vary considerably in various countries, regions and herds over time. In Finland, the prevalence of porcine respiratory pathogens differs substantially from the situation in continental Europe. The country has been free of ADV, PRCV and PRRSV for decades. Also, Finland is nearly free of swine enzootic pneumonia. In 2015, MHyo was detected in only one Finnish pig herd , and mosThe objective of our study was to clinically and etiologically investigate acute outbreaks of respiratory disease in Finland. This field study also aimed to evaluate the clinical use of various methods in diagnosing the respiratory infections under field conditions and to describe the antimicrobial resistance profile of the main bacterial pathogen(s) found during our study.This case-control study was carried out between May 2011 and January 2014 in finishing or farrow-to-finish pig herds in southern and southwestern Finland. Practicing herd veterinarians and herd owners in the area were asked to contact the research group when acute respiratory symptoms became apparent in finishing pigs. Veterinarians were informed of the study via several emails, letters and at veterinary meetings along with an announcement in the Finnish Veterinary Journal. Herd owners were informed at farmer meetings organized by the major slaughterhouses. Case herds were included in the study if they had at least one pig room with finishing pigs displaying a cough, fever and lowered appetite. A total of 20 case herds were enrolled in our study.N = 8) were selected from herds taking part in another study during the same time period. They were selected as case herds according to similar geographical location, herd size and type (fattening and/or farrow-to-finish). The control herds consisted of herds where local practicing veterinarians regularly clinically checked for signs of disease, at least every 3 months, and no acute respiratory signs were diagnosed in the finishers at the time of our study.Control herds  days after the owner first observed the clinical signs and 26 (SD 13) days after the pigs had arrived to the fattening room. The second visit to case herds occurred 33 (SD 5) days after the first visit. The first visit to the control herds occurred 22 (SD 21) days after the feeder pigs arrived at the finishing rooms and the second visit was conducted 58 (SD 16) days later.If a case herd had more than one room designated for finishers, the room exhibiting the most severe respiratory symptoms was selected for sampling. With the control herds, the room housing feeder pigs that had arrived 1–3 weeks earlier was selected. At the beginning of the first herd visit, each pig in the room was forced to stand up while researchers counted the number of coughing and sneezing episodes in the room for 5 min. A coughing/sneezing episode was defined as a single cough/sneeze or a set of continuous coughing/sneezing by a single pig. For the incidence ratio calculations, the number of sneezing and coughing episodes was related to the number of pigs in the room (number of episodes per 100 pigs for 5 min). In the case herds, farmers were also instructed to mark pigs displaying respiratory symptoms with colour markings before the herd visit. These pigs along with the ones observed coughing during the herd visit were selected for sampling. In both the case and control herds, 20 pigs were caught with a snout snare, their rectal temperature was measured and they were ear-tagged and blood-sampled for serological investigations of APP, SIV, MHyo, PRRSV and PRCV. In addition, nasal swabs were taken from 20 pigs in the case herds for SIV determination by PCR. Control herd pigs were clinically free from respiratory symptoms. They were examined for acute SIV infection only serologically, with paired serum samples, as SIV is known to be only found in nasal discharge during the acute phase of infection . We estiIn the case herds, three non-medicated pigs (13–14 weeks of age on average) with the most evident respiratory signs were euthanized and necropsied during the first herd visit. A lung and the heart of these pigs were sent to a laboratory for pathological, virological and bacteriological analyses, including antimicrobial susceptibility testing. No exact records of past usage of antimicrobial medication of case herds were available. No control herd pigs were available for necropsy.The second visit to each herd included an interview with the owner, a count of the coughing and sneezing episodes of the pigs in the same room as during the first herd visit, and rectal temperature measurement and blood sampling of the ear-tagged pigs.The nasal swabs were inserted in a transporting media  and surrounded with chilling gel packs before transportation to a laboratory, where they were analysed the next day. All blood samples were cooled to 4 °C and centrifuged at 3000 rpm for 10 min within 24 h after sampling. The sera were stored frozen in −18 °C until analysis. The lungs and hearts of the euthanized pigs were chilled with icepacks, sent to a laboratory and examined the next day. PCV2 analyses were performed in the laboratory of CReSA, Spain. All other analyses were conducted in the laboratory of the Finnish Food Safety Authority (Evira).A total of 60 lung samples from euthanized pigs from 20 case herds were examined. Gross lesions in the lungs including consolidation, abscesses and fibrinous or fibrotic pleurisy and other findings were recorded. Tissue samples were taken from the affected areas in the lungs. The samples were fixed by immersion in 10% neutral formalin, embedded in paraffin, cut in 4-μm thick sections and stained with haematoxylin and eosin. Lung tissue samples were additionally taken, especially from pneumonic lesions, were submitted to bacteriological examination and a sample of the lung tissue was also submitted to be PCR-tested for SIV. These macroscopic lung lesions together with histological and bacteriological results were used to classify the herds.Haemophilus parasuis isolation, the samples were cultivated on bovine blood agar with a Staphylococcus aureus streak and incubated under a 5% CO2 atmosphere at 37 °C. The small colonies showing enhanced growth around the S. aureus streak were isolated and confirmed by a positive Camp reaction. They were tested using multiplex PCR, which identified the species and APP serotypes 2, 5 and 6 [Haemophilus parasuis using biochemical tests . All APP isolates obtained were tested for antimicrobial susceptibility.For aerobic pathogen detection, the lung tissue samples were cultivated on bovine blood agar and incubated at 37 °C. In addition, for possible APP biotype 1 and  5 and 6 . The nonThe antimicrobial susceptibility of the APP isolates was determined using a broth microdilution method  and a disk diffusion method  following the Clinical and Laboratory Standards Institute (CLSI) guidelines . SusceptN = 60) and nasal swab (N = 400) suspensions using a QiaAmp ViralRNA Mini Kit . All samples used for virus detection were subjected to influenza A M-gene-specific real-time RT-PCR [SIV RNA was extracted from the lung  on the Bio Sprint 96 system (Qiagen). Positive and negative extraction controls were added to each extraction plate. DNA samples were processed by means of a standard PCV2 PCR method . NegativThe case herds were classified according to the pathology, bacteriology and virology of the three lung samples examined from each herd and the nasal swab samples examined for SIV.A herd was considered to suffer from acute respiratory disease caused by APP (coded as CL-APP) when pigs examined pathologically exhibited either 1) typical pathological gross lesions for APP  in at least two out of the three lung samples together with isolation of APP bacteria in two or three lung samples, or 2) characteristic pathological lesions in at least one lung sample and either a necrotic area indicative of APP infection or mild consolidated lesions in another lung sample combined with isolation of APP bacteria in all three lung samples.Ascaris suum (coded as CL-ASC) infestation when the following two criteria were fulfilled: 1) at least two out of the three pigs examined pathologically in these herds had compatible gross lesions  compatible with an A. suum infestation, and 2) detection of gross ascarid larvae in the tracheal froth and/or in the histological sections of these lung samples. The lung samples defined as having lesions caused by an A. suum infestation had no other gross lesions characteristic of another specific respiratory pathogen.A herd was considered to suffer from respiratory disease caused by an acute A case herd was considered to suffer from acute swine influenza infection (coded as CL-SIV) if SIV was detected by PCR in at least one of the three examined lungs or in at least one of the 20 nasal swab samples.Miscellaneous etiology (coded as CL-MISC) was considered if variable pneumonic lesions in the lung samples were observed and the abovementioned criteria were not fulfilled.In the laboratory, we analysed samples of the first 15 pigs out of the 20 collected with paired samples available from both herd visits. APP antibodies were measured using two commercial test kits: IDEXX APP-ApxIV ELISA  to detect antibodies against ApxIV toxin, which is produced by all known APP serotypes (19), and IDvet ID Screen APP 2 indirect ELISA  to detect antibodies against lipopolysaccharides (LPS) specific to APP serotype 2 (APP2) with a sensitivity of 82.9% and a specificity of 99.6% for IDEXX APP ApxIV Elisa and a specificity of 99.68% for IDVet APP2 Elisa. Both tests were performed according to the manufacturer’s instructions. The absorbance values (percentage of positive control) from the paired samples were compared. Seroconversion at the individual pig level was defined as an increase in absorbance. A herd was considered to suffer from an acute APP infection if at least one individual pig seroconverted based on at least one serologic test (ApxIV toxin or APP2 LPS) between the herd visits.The samples of the first 15 pigs out of the 20 collected with paired serum samples available from both herd visits available were analysed from each herd. All blood samples were tested with influenza A antibody ELISA  according to manufacturer instructions. A sample was considered unclear when the competition percentage (S/N%) was 46–49% and positive when the competition percentage was ≤45%. If a herd had at least one unclear or positive blood sample (pig) in the ELISA test in either of the samplings (first or second), blood samples of that herd were further analysed using a hemagglutination inhibition (HI) test according to European Surveillance Network for Influenza in Pigs [Ten serum samples collected from the case herds during the second herd visit were examined for antibodies against MHyo. The antibodies were detected using a blocking ELISA commercial kit , following manufacturer’s instructions. Samples with an optical density value less than 50% of the OD buffer control were interpreted as positive. The sensitivity and specificity of the ELISA test was 100% and 98%, respectively.Serological screening for PRCV and PRRSV were carried out in 12 samples collected from each case herd during the second herd visit. A commercially available TGEV/PRCV ELISA test  with a sensitivity of 93% and specificity of 97% and PRRSV  with a sensitivity of 98.8% and specificity of 99.9% were used according to the manufacturers’ instructions. The PRCV test result was interpreted as negative when the percent inhibition was <45 and PRRSV test result negative when the S/P ratio was <0.4. A farm should be considered positive for PRRSV or PRCV if one or more samples were judged positive.p-value <0.05 was used.All statistical data analyses were performed using Stata 14.0  and the statistical significance of Body temperature of the studied case and control herd animals was compared using unconditional linear regression. Prevalence of clinical signs (coughing and sneezing) during the first and second herd visits and in the case and control herds were modelled as count data (number of coughing/sneezing episodes per 5 min) using a Poisson or negative binomial model.The percentages of PCR-positive samples in serum (PCV2) were compared between the case and control herds using the Wilcoxon rank sum test, because the proportion was not normally distributed.The proportion of APP and SIV seroconverted animals were calculated for both tests in each herd and compared between the case and control herds using unconditional linear regression. Herd status (acute APP or SIV infection yes/no) based on the serological results was compared between the case and control herds using the chi square test.Out of the 20 case herds, 19 had fatteners only and one was a farrow-to-finish herd. Case herds had an average of 901 (SD 511) fatteners per herd and 234 (SD 101) pigs in each room. The control herds consisted of six fattening and two farrow-to-finish herds with an average of 1075 (SD 400) fattening pigs per herd and 265 (SD 167) pigs per room. In the case and control herds, the pigs originated from an average of 3.7 (SD 6.4) and 1.1 (SD 0.3) different piglet-producing herds, respectively. The season of the first herd visit was relatively similar in case and control herds: spring 20% of case vs. 0% of control herds, summer 20% vs 25%, autumn 25% vs. 50% and winter 35% vs. 25%. Most of the herd visits were done during the year 2012 (60% of case and 62% of control herds), because that was the time when farmers and practicing veterinarians were actively informed about the project.N = 448) and 39.4 °C  in the case and control herds, respectively (p = 0.01). Corresponding figures for the second herd visit were 39.3 °C  and 39.3 °C  (p = 0.3) for the case and control farms, respectively.Average rectal temperatures of the pigs during the first herd visit were 39.7 °C  and 0.2  coughing episodes were counted per 100 pigs during the first herd visit. The incidence rate ratio (IRR) for coughing episodes (case vs. control herds) was 16.5 (p < 0.01) during the first herd visit. By the second visit the coughing episodes in the case herds decreased to the same level as in the control herds: 0.6 (SD 0.8) for the case rooms and 0.4 (SD 0.5) for the control rooms. No difference in IRR was observed for the coughing episodes during the second herd visit .An average 4.0  during the first herd visit. By the second visit, the sneezing episode count in the case herds had decreased down to the same frequency as in the control herds: 5.5 (SD 4.4) in the case herds and 3.9 episodes per 100 pigs in the control herds .During the first herd visit, case pigs averaged 12.2 sneezing episodes per 100 pigs (SD 11.1) and the control pigs averaged 5.5 (SD 5.3). The IRR for sneezing episodes (case vs. control herds) was 1.9 (A. suum infections (CL-ASC) based on the examination of lung samples. Two of the latter herds also had APP seroconverted pigs, and one of these two herds had gross lesions caused by APP in one lung sample.Fourteen (70%) out of 20 case herds were classified as having respiratory infection caused by APP (CL-APP) based on the pathological and bacteriological results. Three case herds were classified with a miscellaneous (CL-MISC) respiratory infection unassociated with a specific pathogen and three other herds (15%) were diagnosed to suffer from acute Escherichia coli, P. multocida, S. aureus, Actinomyces spp., Streptococcus dysgalactiae subs. Equisimilis, S. suis and Streptococcus spp. and gram- and CAMP-negative and NAD-dependent rodbacterium. The PCR testing showed all APP cultures to be APP serotype 2.Bacterial pathogens were isolated from the pig lungs of 18 (90%) case herds. Of these, 12 (66%) herds had APP only (11 of these herds were classified as CL-APP herds and one as a CL-ASC herd). Four herds (22%) had APP together with another bacteria (three of these herds were classified as CL-APP and one as CL-MISC herds) and two (11%) only had other pathogens . No specific bacteria were detected in the pig lungs from two farms (10%). Other encountered bacteria included A herd-level summary containing relevant pathological, virological and serological results is presented in Table All lung and nasal swab samples were SIV negative. Thus, none of the case herds was diagnosed to suffer from acute SIV infection based on PCR even though some herds were serologically positive.Forty-four APP isolates obtained from 16 case herds were tested for antimicrobial resistance. APP isolates from six herds 38%) were intermediately resistant and one herd (6%) tested resistant to tetracycline. Isolates from one herd (6%) were intermediately resistant while two herds (13%) had isolates resistant to trimethoprim/sulfamethoxazole. Isolates from two herds (13%) were resistant to ampicillin and penicillin. Altogether, five isolates resistant or intermediately resistant to at least two different antimicrobials were detected from three herds. No resistance to florfenicol, enrofloxacin, tiamulin or tulathromycin was found. Minimum inhibitory concentration (MIC) distribution is presented in Table 8% were ip = 0.1). Seroconversion to ApxIV toxin was detected in 68.8% (SD 26.7) of the individual animals in the case herds and in 67.5% (SD 43.7) in the control herds. Seroconversion to APP2 LPS was detected in 38.3% (SD 27.9) of individual animals in the case herds and in 38.9% (SD 27.8) in the control herds. No difference was found in the proportion of seroconverted animals between the case and control herds .Antibodies to ApxIV toxin were detected during the first sampling in 14 (70%) case and six (75%) control herds. Respectively, APP2 antibodies were found in six (30%) case and five (62.5%) control herds. Seroconversion to either ApxIV toxin or APP2 LPS was detected in at least one pig in 19 (95%) case herds and six (75%) control herds. These 19 case and six control herds were classified to suffer from an ongoing acute APP infection based on the serology results. No difference was observed in the occurrence of acute APP infection between the case and control herds (p = 0.5). On average, 5.9% (SD 9.1) of individual animals had seroconverted in the case herds and 8.5% (SD 12.8) in the control herds based on the HI test. No difference was found in the proportion of seroconverted animals between the case and control herds (p = 0.7).During the first sampling, SIV antibodies were found in pigs in eight (40%) case and three (37.5%) control herds. Three out of 20 case (15%) and two out of eight control (25%) herds were classified with an ongoing acute SIV infection at the time of the herd visits based on the seroconversion of at least one sampled pig. No difference was found in the number of acute SIV herds between the case and control herds  case herds and two out of eight (25%) control herds had at least one PCR-positive serum, respectively. A total of 29 PCV2 PCR-positive samples with mean percentage of positive samples per herd 9.7% (SD 18.2) were detected in the case herds and one positive  in each control herd. No difference was observed in the proportion of PCV2 PCR-positive samples between the case and control herds.Actinobacillus pleuropneumoniae was the most common cause of acute respiratory outbreaks in the studied finishing pig herds. However, SIV, Ascaris suum, PCV2 and certain opportunistic bacteria appeared to cause concurrent infections, potentially contributing to the respiratory disease outcome. SIV and PCV2 were detected also in control herds suggesting possible subclinical infections in these herds. Serology alone was not effective in determining the cause of a respiratory outbreak, but pathology and bacteriology were considered useful in reaching a complete diagnosis. In addition to this, bacteriology together with antibiotic resistance determination was valuable in selecting the correct medication to be used, which is important in practice.Clinical examination of the case herd pigs revealed respiratory signs including higher rectal temperature and coughing when compared to the control herd pigs. We were unfortunately unable to acquire exact data on the mortality in the rooms, because some animals in several herds were moved before or between herd visits to other rooms housing sick animals. However, the clinical signs in the herds were quite mild compared to those reported in experimental studies . During A. suum.APP2 was the main causative agent for acute respiratory infections in Finnish finishing pigs. Previous Finnish studies screening the APP serotypes present in the country have revealed that APP2 is a common serotype together with several others , 24. HowIt is difficult to compare the role of APP in respiratory infections in various countries, as study herds have usually not been selected and sampled in the same way as in our study. A study on clinical outbreaks carried out in the Netherlands in a manner similar to ours found APP to be the most likely cause in five out of 16 clinical outbreaks . Other rSerology has indeed been used in several studies examining APP causing respiratory infections in finishing pigs, but serological results have usually not been connected to clinical findings or acute outbreaks. Herds e.g. in Spain , Italy , Canada E. coli, P. multocida, S. aureus, Actinomyces spp., S. dysgalactiae subs. Equisimilis, S. suis and Streptococcus spp. APP serology showed seroconversion in each of these herds. SIV seroconversion additionally happened in one herd. Other researchers have also found that reaching a proper diagnosis is not always easy under field conditions despite using several diagnostic methods. Researchers studying respiratory outbreaks in 16 herds in the Netherlands could not reach a definitive diagnosis in four herds [Three out of 20 outbreaks had a miscellaneous etiology. The pathology and bacteriology of these herds revealed findings incompatible with the set criteria for acute APP or SIV infections and the presence of bacteria such as APP, ur herds . They coAscaris suum infection was found to be the main cause of respiratory clinical signs in three case herds (15%). At least in Finland this pathogen has been considered a minor disease agent, especially in modern management systems with concrete floors and without outdoor access. It is widely known that A. suum can cause verminous pneumonia, as the larvae migrate through the lung tissue during their lifecycle [A. suum infestations . Liver condemnations due to milk spots caused by A. suum were recorded in an average 6.5% of the finishing pigs slaughtered during the years 2010–2015. Other, more specific diagnostic methods for ascarids, have shown the prevalence of this parasite to be high. For example, antibodies against A. suum were observed in 39% of the study herds in a Danish study on finishing pigs [A. suum positive [ifecycle . Also, sing pigs . A highepositive . Ascariapositive  and impapositive . Also, pViral pathogens appeared to be less important as a cause of acute respiratory symptoms in finishing pigs in our study. The significance of SIV infection varies in other studies. For example, a clinical field study in the Netherlands showed SIV to be the most frequent main cause of a clinical outbreak in 16 herds . In a rePCV2 has been associated with several disease syndromes collectively named porcine circovirus diseases . The rolAccording to our hypothesis, certain pathogens causing acute respiratory symptoms in pigs, namely Mhyo, PRRSV and PRCV, were not found in the studied Finnish herds. Especially Mhyo and PRRSV are important pathogens involved in respiratory infections in many pig-producing countries despite PRRSV not being detected in certain countries e.g. Finland , 24, 43.The vaccination history of study animals may have had some influence on serological results. We do not know the exact vaccination scheme utilized for study animals. However, we know that at the time of the study, Finnish sow herds generally vaccinated all sows against erysipelas, parvovirus and colibacillosis and a vaccination of piglets against PCV2 is very common in the country. We also know that very few (most likely none of the herds in our study) herds vaccinated against APP or SIV. Based on that estimation, it is unlikely that vaccinations would have had any significant effect on APP serology.In our present study, APP strains were susceptible to most of the tested antimicrobials. Only tetracycline resistance was detected in more than 10% of the isolates. Similar results have been found in other European countries. Thus, resistance to tetracycline among porcine APP is a growing problem. Other studies have occasionally observed resistance to penicillin, ampicillin and trimethoprim/sulfamethoxazole –49. The From a practical standpoint, the field necropsies supplemented with microbiological analysis was the most valuable diagnostic tool combination for detecting the main cause of acute respiratory infections in our study. Field necropsies have several advantages: the technique is simple, inexpensive and not pathogen-specific, preliminary results are promptly available and antimicrobial susceptibility results can be obtained from bacteria isolated from lesions. However, field necropsies are disadvantageous, since if acute disease is not leading to mortality, euthanasia should be performed. In acute respiratory outbreaks, field necropsies, sample-taking and antimicrobial susceptibility testing are extremely important, because resistance to certain recommended antimicrobials does exist. Susceptibility testing is necessary not only from the field veterinarian’s and single pig herd’s point of view, but also from a national policymaker’s perspective. Serology cannot be used alone in diagnosis, but offers detailed information about possible pathogens causing mainly subclinical infections. Also other diagnostic methods could be used. In addition to the already mentioned oral fluids, tracheobronchial swabs  or lavagA. suum or other opportunistic bacteria caused acute coughing episodes in some herds. Viral pathogens appeared to have a minor role in causing the clinical signs. Field necropsies supplemented with microbiological analysis were the most valuable diagnostic tool combination in detecting the main cause of the infections under field conditions. Bacterial isolation from the lungs was especially important in assessing antimicrobial susceptibility and for optimizing antimicrobial treatment, because some resistance, especially to tetracycline, was found among the APP strains causing disease. Serological diagnostics were not optimal in the diagnosis of the respiratory outbreaks of our study. Although several different diagnostic methods were used, the primary pathogen causing the outbreak remained questionable in some herds.APP serotype 2 was the most common cause for acute respiratory outbreaks in finishing pigs in Finland and


Rhodopseudomonas palustris is a versatile microbe that encounters an innate redox imbalance while growing photoheterotrophically with reduced substrates. The resulting excess in reducing equivalents, together with ATP from photosynthesis, could be utilized to drive a wide range of bioconversions. The objective of this study was to genetically modify R. palustris to provide a pathway to reduce n-butyrate into n-butanol for maintaining redox balance.n-butanol production from Clostridium acetobutylicum ATCC 824 in R. palustris. We maintained the environmental conditions in such a way that this pathway functioned as the obligate route to re-oxidize excess reducing equivalents, resulting in an innate selection pressure. The engineered strain of R. palustris grew under otherwise restrictive redox conditions and achieved concentrations of 1.5 mM n-butanol at a production rate of 0.03 g L−1 day−1 and a selectivity  of close to 40%. Since the theoretical maximum selectivity is 45%, the engineered strain converted close to its maximum selectivity.Here, we constructed and expressed a plasmid-based pathway for R. palustris can be used to drive the reduction of n-butyrate into n-butanol after expression of a plasmid-based enzyme from a butanol-producing Clostridium strain.The innate redox imbalance of The online version of this article (doi:10.1186/s13068-017-0864-3) contains supplementary material, which is available to authorized users. Rhodopseudomonas palustris, which is a member of the purple non-sulfur bacteria group, is often noted for its metabolic versatility. One of these metabolic activities, which is H2 production by photofermentation, utilizes organic carbon under anaerobic conditions with light and has become an attractive application for bioenergy production [2 at high concentrations is driven by an excess of reducing equivalents that accumulate during photoheterotrophic growth [n-butanol (hereafter butanol).oduction . The abi2 fixation, H2 evolution, or a combination of both. These two pathways were found to be complementary in this role, and when one route was made unavailable, the other facilitated the re-oxidation of all reducing equivalents with minimal changes occurring elsewhere in the central metabolism. However, when fed a more reduced substrate, such as n-butyrate (hereafter butyrate), it was observed that under non-H2 evolving conditions, R. palustris could only grow if exogenous CO2 was supplemented into the medium [R. palustris generates more reducing equivalents than available electron sinks can accommodate, and ultimately suffers a lethal redox imbalance. Numerous studies have used these principles to improve H2 yields from photofermentation using R. palustris [When growing on acetate, McKinlay and Harwood  reportede medium . This fialustris –6.R. palustris to utilize excess reducing equivalents to reduce CO2 into CH4 by remodeling the nitrogenase enzyme active site and expressing the modified gene from the chromosome. A NifA* strain of R. palustris was chosen as the host because it expresses the nitrogenase gene constitutively even in the presence of NH3. The result was a light-dependent R. palustris strain that produced CH4 with ATP coming from cyclic photophosphorylation and electrons coming from either an organic substrate or thiosulfate. This reduction is, however, not obligatory and a large excess of H2 was produced by the nitrogenase compared to CH4 [Recently, Fixen et al.  engineerd to CH4 . AnotherClostridium acetobutylicum ATCC 824, which has been widely studied for this activity, is generally seen as the model organism for solvent production and previously has been used as a source of genes for engineered butanol production [C. acetobutylicum, reduction of butyrate proceeds through a two-phase pathway. First, butyrate is activated to butyryl-CoA, which can occur by two different routes: (1) a two-step butyrate kinase/phosphotransbutyrylase reaction  reduces butyryl-CoA to butyraldehyde and subsequently butanol  into R. palustris  due to the major incompatibilities in codon utilization preference between the C. acetobutylicum source and the R. palustris host. Therefore, we pursued two alternate attempts to introduce the activity of AdhE2 by using: (1) a gene homologous to adhE2824 from R. palustris strain BisB18 (hereafter adhEBisB18 and AdhEBisB18 for its protein); and (2) a codon-optimized adhE2824 (hereafter adhE2opti and AdhE2opti for its protein). In all our growth experiments, we omitted HCO3− (CO2) from, and added NH3 to, the growth medium to block the normal routes of shunting reducing equivalents, resulting in an obligate butyrate reduction. This strong selection pressure will only allow growth when butanol production occurs. In our hands, butanol production through the homologous AdhEBisB18 did not work, but AdhE2opti enabled recovered growth through butanol production. Subsequently, we were able to increase the butanol selectivity and production rate in further experiments, accomplishing our aim of generating an engineered reduction reaction for the obligate production of the liquid fuel butanol in R. palustris.A direct introduction of plasmid-based Rhodopseudomonas palustris CGA009 was cultured in anaerobic butyrate Rhodospirillaceae medium (RM) [3, 0.5 g KH2PO4, 0.5 g K2HPO4, 0.2 g MgSO4·7 H2O, 0.4 g NaCl, 0.05 g CaCl2·2 H2O, 0.01 g Fe-Citrate, 1.0 g (NH4)2SO4, 1.12 mL 10 M NaOH, and 1 mL trace metals per liter. The trace-metal solution consisted of 0.25 mL concentrated HCl, 70.0 mg ZnCl2, 100.0 mg MnCl2·4 H2O, 60.0 mg H3BO3, 200.0 mg CoCl2·6 H2O, 20.0 mg CuCl2·2 H2O, 20.0 mg NiCl2·6 H2O, and 40.0 mg Na2MoO4·2 H2O L−1. After autoclaving, 1.0 g sterile butyric acid was added as the substrate. No toxicity or inhibition of R. palustris growth was detected at this concentration  with a final pH of 7.0 was added to autoclaved serum bottles and sparged for 20 min with sterile-filtered 80:20 N2/CO2 gas. For the growth of engineered strains under restrictive butyrate-to-butanol conversion conditions, NaHCO3 was omitted from the medium, the addition of 10 M NaOH was increased to 2.3 mL total, and serum bottles were sparged for 20 min with N2 instead of N2/CO2. In addition, 200 μg mL−1 of kanamycin sulfate was added for retention of the plasmid in all growth conditions with engineered strains. All serum bottle cultures were grown in an environmental growth chamber  at 30 °C with 80 μmol of photosynthetically active photons s−1 m−2 (photons between 400 and 700 nm) illumination from both fluorescent and incandescent lamps.ium (RM) , consistR. palustris under aerobic conditions. We tested two different plasmids as candidate expression vectors: (1) the endogenously derived pMG105 [prior to the termination site with PCR by the reverse primer  from R. palustris, arabinose (ara), and lactose (lac) promoters. The adhEBisB18 and adhE2824 genes were amplified from R. palustris strain BisB18 and C. acetobutylicum ATCC 824, respectively, using Phusion HF polymerase  and directionally ligated into the pBBR1MCS-2 expression vector using the XhoI/XbaI cloning sites. Restriction and ligation enzymes were purchased from Promega  and all constructs were verified with Sanger sequencing . Escherichia coli DH5α was used for routine cloning of constructs. Both E. coli and R. palustris were transformed by electroporation with a Bio-Rad Gene Pulser II Electroporator  with 1.8 kV, 200 Ω, 25 µF for E. coli, and 2.5 kV, 400 Ω, 25 µF for R. palustris. Electroporated cells were recovered in SOC for 1 and 3 h before plating on lysogeny broth (LB) agar plates with 50 and 200 μg mL−1 kanamycin sulfate for isolation of individual E. coli and R. palustris transformants, respectively.We used the green fluorescence protein GFPmut2  as a repd pMG105 ; and (2)d pMG105 . For det824 in R. palustris, codon optimization was pursued. Optimization design was performed in-house and largely utilized the one amino acid one codon approach, except in cases of multiple codon repeats and unfavorable energetics of mRNA secondary structure  with flanking XhoI/XbaI restriction sites that were used for directional cloning into pBBR1MCS-2.To successfully produce AdhE2E. coli and R. palustris cells were harvested by centrifugation  and resuspended in 1 mL 1X Laemmli sample buffer [−1 soluble protein samples and 10 μL of Precision Plus Protein™ standard  were loaded into pockets of a Mini-PROTEAN® TGX gel  and run at 100 V for 1.5 h before blotting onto PVDF membranes at 100 V for 1 h. For the initial western blot, immunoreactive bands were developed using manufacturer-suggested protocols for the 1 h Western™ Standard Kit for rabbit  and a 6X His primary antibody . We used a similar protocol a second time to improve the sensitivity with these changes: we used 0.1 mL OD600 1.0 cells with 0.1 mL Laemmli sample buffer. The samples were boiled for 10 min before centrifugation. 15 µL of each sample was loaded into separate gel lanes. For development, an enhanced chemiluminescence protocol was used using the manufacturer-suggested protocol for promega ECL western blotting substrate . The film was allowed to incubate with the PVDF membrane for 30 min prior to development.For both SDS-PAGE and subsequent western blot detection, 50 mL of late-log e buffer  with a pPrior to operation, sealed glass bioreactors were autoclaved and filled with 350 mL sterile RM with 1 g L−1 butyrate and without HCO3−. The bioreactors were equipped with a recirculating water jacket that was operated at 30 °C. Magnetic stir plates  provided stirring of the reactors at 450 rpm. The bioreactors were continuously sparged with sterile-filtered N2 gas at a flow rate of 0.1 L min−1 to maintain an anaerobic environment. After sparging for 1 h to ensure anaerobic reactor conditions, 1 mL of actively growing R. palustris cells at an OD600 of 0.1 was inoculated into the bioreactor. The preculture of R. palustris pBBR1MCS-2 lacp adhE2opti was grown in anaerobic RM without HCO3−, while the preculture of R. palustris pBBR1MCS-2 lacp GFPmut2 (control) was grown in aerobic RM without HCO3−. Gas entered the liquid phase of each bioreactor through a sparging stone to increase the gas/liquid interface for butanol stripping. Off-gas was connected to 2 Friedrich’s condensers in parallel with recirculating water at 5 °C to condense the butanol that had been removed by gas stripping. Gas was released into the atmosphere after one passing through the condensers. The bioreactor volume was illuminated externally with a single 60-W incandescent lamp as used previously [600 and metabolite measurements.eviously . The bio−1 was used as the mobile phase. Butanol and butyraldehyde were measured with a gas chromatograph  with a 7673 autoinjector and flame ionization detector. The gas chromatograph contained a custom-made packed bed glass column of 1.8 m × 2 mm id . The support matrix of the column was Chromosorb W/AW80 over 100 mesh; phases were preconditioned: phase A was 10% Carbowax-20M; phase B was 0.1% phosphoric acid. The inlet and detector temperatures were 220 and 240 °C, respectively. The column temperature profile was 100 °C for 2 min, a ramp of 40 °C min−1 to 180 °C with a 5-min hold. Butanol concentrations were verified by both HPLC and GC platforms.Butyrate, butanol, and acetate were measured via HPLC  with a refractive index detector and an Aminex HPX-87H column . The column temperature was set to 60 °C, and a 5-mM sulfuric acid eluent at a flow rate of 0.6 mL minR. palustris. The endogenous ppckA promoter of R. palustris is one of the few promoter sequences that had been previously validated to be active in R. palustris under gluconeogenic conditions [ppckAp GFPmut2 constructs compared to the empty vector controls .Different combinations of promoter and vector sequences were screened for highest levels of expression within nditions . HoweverBisB18 Aerobic), direct introduction of adhE2824 in the pBBR1MCS-2 lacp construct did not result in the production of AdhE2824 in R. palustris. This is likely due to the large GC discrepancy (30% vs. 65%) and codon utilization preference between C. acetobutylicum and R. palustris [R. palustris. Indeed, endogenous alcohol/aldehyde dehydrogenases with homology to AdhE2824 have been found to function in the production of butanol from butyrate when overexpressed. This was previously demonstrated with the fucO gene in E. coli, where overexpression allowed production of butanol from an engineered reverse β-oxidation pathway where no butanol production was observed previously [R. palustris, a BLAST search for an endogenous enzyme yielded the identification of RPC_4481 (AdhEBisB18) in R. palustris strain BisB18, which is an aldehyde/alcohol dehydrogenase with high homology to both domains of AdhE2824.As determined by the lack of growth under restrictive conditions, the absence of butanol production (data not shown), and the lack of a signal in a western blot under permissive conditions . Although no growth or butanol production occurred (data not shown), it is possible that wild-type production of this protein under these conditions is either inactive or insufficient for an observable effect, similar to the FucO protein in E. coli [BisB18, its highly conserved primary sequence was further investigated for its structural homology to the verified butanol-producing AdhE2824.Before expressing  E. coli . Because824 and AdhEBisB18 were generated. The predicted tertiary structure of both aldehyde/alcohol dehydrogenases appeared highly conserved with regard to overall shape, location, active site residues, channel volume, and surface charge , suggesting that either AdhEBisB18 was not successfully produced by R. palustris CGA009 or did not have butyryl-CoA-to-butanol conversion activity.Using Swiss-Pdbviewer/DeepView , three-d3−, along with E. coli harboring the same construct, was analyzed via western blotting. Although the strong signal at the expected size of 94.5 kD for AdhEBisB18 for E. coli pBBR1MCS-2 lacp adhEBisB18 demonstrated that the protein was produced , the lack of a signal from R. palustris pBBR1MCS-2 lacp adhEBisB18 suggested that the protein was either not produced or was produced at levels below detection . Aerobic conditions were preferred since anaerobic cultures often had photosynthetic pigments overlapping the expected size for AdhE . The lack of growth and butanol production under restrictive conditions, however, demonstrated conclusively that R. palustris pBBR1MCS-2 lacp adhEBisB18 was not endowed with butyrate-to-butanol conversion functionality (data not shown).To investigate this further, a crude cell extract of the culture with HCOC. acetobutylicum and R. palustris was to perform codon optimization on adhE2824 to enable expression. The codon utilization table for R. palustris CGA009 was determined by analysis of all genomic coding sequences and was retrieved from the Kazusa database [adhE2opti gene resulted in an increase of the average codon utilization frequency in R. palustris from 23% for the original adhE2824 to 64% for the optimized adhE2opti , which previously composed 47.4% of all codons in adhE2824, was entirely eliminated. One disadvantage to this approach of codon optimization is that rare codons are known to induce ribosomal pausing, which has been demonstrated important for proper folding of proteins. Thus, with the elimination of all rare codons from adhE2opti, the elimination of codon-dependent ribosomal pausing could lead to improper folding and aggregation of the target protein [adhE2opti, the codon utilization frequency of adhEBisB18 averaged 55%  and it produced a measureable amount of butanol, demonstrating the successful production of AdhE2opti with a functional activity. While a detectable signal was observed on a western blot for the E. coli cloning culture, no signal was initially detected from R. palustris pBBR1MCS-2 lacp adhE2opti . We performed a second western blot using a more sensitive X-ray film imaging method. For aerobically grown R. palustris pBBR1MCS-2 lacp adhE2opti, we observed a single signal at approximately 94 kD, demonstrating successful expression . As stated above, GFPmut2 production from the pBBR1MCS lac promoter is much lower in R. palustris than in E. coli, so the lack of a signal in the majority of the samples is likely due to low protein production in R. palustris.To test whether R. palustris pBBR1MCS-2 lacp adhE2opti was further investigated for its ability to grow under both permissive and restrictive conditions and these results were compared to R. palustris pBBR1MCS-2 lacp GFPmut2 as a control. R. palustris pBBR1MCS-2 lacp adhE2opti was capable of growth without HCO3− (restrictive conditions)  Fig. b, while 600 Fig. b at neut600 Fig. d. Follow600 Fig. f, h, but600 Fig. h.Fig. 4P2) for 83% conversion efficiency. However, based on previous empirical measurements of excess reducing equivalents of R. palustris growing with butyrate by McKinlay et al. [R. palustris pBBR1MCS-2 lacp adhE2opti (40% vs. 45%), which we had anticipated for an obligatory reaction.Although only low levels of butyrate were consumed Fig. f, butanoR. palustris pBBR1MCS-2 lacp adhE2opti showed low growth rates, R. palustris was screened for product (butanol) toxicity. However, no inhibition of growth was observed in R. palustris at butanol concentrations up to ~30 mM  when exogenous CO2 was available for maintaining redox balance , the complete depletion of butyrate (Fig. Some butanol production did also occur for nce Fig. a, g at ance Fig. c. Becauspti Fig. a, resultpti Fig. e, g. Thoate Fig. e, no proate Fig. g. This c600 of these cultures was >1. By using a concentrated inoculum, R. palustris pBBR1MCS-2 lacp adhE2opti produced butanol concentrations of greater than 1.5 mM at volumetric butanol production rates of 0.034 g L−1 day−1 (Fig. R. palustris pBBR1MCS-2 lacp adhE2opti culture continued to grow and consume butyrate (Fig. In an attempt to improve the maximum butanol concentrations produced by the engineered strain, 50 mL aerobic cultures was grown to mid-log phase, washed 3 times with sterile RM, resuspended in 0.5 mL RM, and used as an inoculum into 20-mL anaerobic cultures under restrictive conditions. This procedure ensured that the butyrate-to-butanol conversion was not catalyst limited as the initial ODadhE2opti into R. palustris via a plasmid-based construct is an example of metabolically engineered fuel production that proceeds as an obligate strategy for growth. Although growth and production rates were low for this system, our selectivity of 39.7 ± 7.6% matched well with the empirical expectation of 45.0% under these conditions. Because the low growth rates and butanol production are likely constrained by redox flux through the engineered pathway, rational design and directed evolution could be used to further improve the performance of this activity. If improved, the system could be easily integrated into a simple bioreactor design with highly efficient selectivity and recovery. While this proof-of-concept for harnessing an obligate reducing metabolism to drive engineered reactions used butanol as a target molecule, this redox-based driving force could be used to achieve other reactions for the production of desirable chemicals that require reduction reactions.The introduction of Additional file 1. Growth with butyrate, containing Figure S1.Additional file 2. Sequence.Additional file 3. Fluorescence, containing Figure S2.Additional file 4. Structure, containing Figure S3.Additional file 5. Codons, containing Figure S4.Additional file 6. Codons and GC content, containing Table S1.Additional file 7. Growth with butanol, containing Figure S5.Additional file 8. Growth with product removal, containing Figure S6.


The carrier is expressed in mitochondria of fungi, plants and animals and belongs to the family of mitochondrial carriers. The carrier is unusual as it consists of three separate domains: (i) an N‐terminal regulatory domain with four calcium‐binding EF‐hands similar to calmodulin, (ii) a loop domain containing an amphipathic α‐helix and (iii) a mitochondrial carrier domain related to the mitochondrial ADP/ATP carrier. This striking example of three domains coming together from different origins to provide new functions represents an interesting quirk of evolution. In this review, we outline how the carrier was identified and how its physiological role was established with a focus on human isoforms. We exploit the sequence and structural information of the domains to explore the similarities and differences to their closest counterparts; mitochondrial ADP/ATP carriers and proteins with four EF‐hands. We discuss how their combined function has led to a mechanism for calcium‐regulated transport of adenosine nucleotides. Finally, we compare the ATP‐Mg/Pi carrier with the mitochondrial aspartate/glutamate carrier, the only other mitochondrial carrier regulated by calcium, and we will argue that they have arisen by convergent rather than divergent evolution. © 2018 The Authors. IUBMB Life published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 70(12):1222–1232, 2018The mitochondrial ATP‐Mg/P AACADP/ATP carrierAGCaspartate/glutamate carrierAPCI carriersATP‐Mg/PCSNcytoplasmic salt‐bridge network1FOF1FO ATP synthaseFLETM1leucine zipper‐EF‐hand‐containing transmembrane protein1MCUmitochondrial calcium uniporterPiCmitochondrial phosphate carrierMSNmatrix salt‐bridge networkSCaMCshort calcium‐binding mitochondrial carrieri) by ATP synthase i carriers (APC), which transport ATP, with or without magnesium, and ADP in exchange for matrix Pi , establishing their molecular identity and properties for the first time SLC25A24), APC2 (SCaMC3/SLC25A25) and APC3 (SCaMC2/SLC25A23), each of which has several possible splicing variants SLC24A41), which appears to function as a calcium‐independent ATP‐Mg/Pi carrier, as it lacks the N‐terminal regulatory domain APC was first described when residual adenosine nucleotide transport in mammalian liver mitochondria was observed after AAC activity was blocked with its specific and potent inhibitor carboxyatractyloside Broadly, the role of APC is to replenish or deplete the pool of adenosine nucleotides in the mitochondrial matrix in response to high‐ or low‐cellular energetic demands, respectively. The effect of altering the matrix adenosine nucleotide pool in mammalian mitochondria has not been fully resolved. However, oxidative phosphorylation, gluconeogenesis, ureogenesis, mitochondrial protein import, mitochondrial protein folding, mitochondrial DNA transcription, mitochondrial translation and mitochondrial DNA maintenance are all pathways that are influenced by the size of the adenosine nucleotide pool Saccharomyces cerevisiae, knockout of the APC orthologue  leads to higher rates of spontaneous petite formation SLC25A23) knockouts have been studied in mouse liver SLC25A25) knockout in a mouse model SLC25A24) leading to an Arg217His or Arg217Cys substitution have been linked to severe forms of mitochondrial disease related to bone development (Gorlin–Chaudhry–Moss syndrome and/or Fontaine syndrome) In EF‐hands usually form functional pairs, and the regulatory domain of APC has two pairs. As shown by the phylogenetic analysis of human proteins with at least two EF‐hand pairs Fig. , APC regAlthough the APC regulatory domain appears to be distantly related to calmodulin in evolution, the key structural features of calmodulin are similar to those of APC regulatory domains. Furthermore, the structure and mechanism of calmodulin has been extensively characterised There have been several crystal structures of human APC1 regulatory domain in calcium‐bound states , solved by different approaches, which have confirmed a calmodulin‐like domain architecture Each EF‐hand of calcium‐bound APC regulatory domain displays an ‘open’ antiparallel arrangement of α‐helices (L‐shape arrangement), equivalent to that of calcium‐bound calmodulin structures Fig. B 34, 35,There are no crystal structures of the calcium‐free state of the APC regulatory domain, but, based on bioinformatics analysis and modelling based on other EF‐hand structures, a comparative structure has been obtained Fig. B 12. In Sequence alignments provide evidence that the architecture of the APC regulatory domain is conserved across vertebrates, invertebrates, plant and fungi, in most cases having four EF‐hands Fig. . The conArabidopsis thaliana APC Vmax but not the Km for substrate transport in APC, suggesting a non‐competitive mechanism of calcium regulation A putative reason for these differences is to respond to different levels of calcium stimuli. Indeed, calcium signalling does not have the same physiological role between vertebrates, invertebrates, plant and fungi. Furthermore, humans have an array of different isoforms and splice variants, displaying a complex and overlapping tissue‐specific expression profile. Therefore, calcium concentrations required to stimulate adenosine nucleotide transport are different in each case, because the affinity of EF‐hands for calcium binding has been adapted through specific mutations. The calcium concentration for half‐maximal activity has been estimated to be 15–30 μM calcium for yeast APC Relative to calcium activation of the AGC (from rat liver), which has been measured at around 300 nM The carrier domains of APC and AAC share significant sequence identity (33% between human APC1 and human AAC1). Furthermore, phylogenetic analysis of all human mitochondrial carriers shows that APCs and AACs cluster closely, with a common branch point in evolution Fig. . MembersMitochondrial carriers have been proposed to function according to a ‘single binding centre gated pore mechanism’ Some mitochondrial carriers, such as AAC, are strict exchangers of substrates animalia kingdom also share the consensus sequence of Px[ED]xx[RK] for the first two repeats of the motif, however, in the final repeat, the negatively charged residue on H5 is replaced with an alanine residue. This network has the potential to form only two salt‐bridge interactions, but it has two out of the three possible glutamine braces, providing at total of 2.5  The protein that shares the most similarities with APC in terms of its combination of domains and its mechanism of action is AGC. Like APC, AGC displays a calcium‐dependent stimulation of activity in its carrier domain The combination of different domains in APC represents an interesting example of evolution. Domains from different evolutionary backgrounds have been combined in order to regulate substrate transport. There are other examples of EF‐hand‐containing proteins that have this type of ‘self‐sequestered’ interaction de novo evolution. APC represents an example of this type of evolution, combining an archetypal mitochondrial AAC‐like carrier domain and an EF‐hand containing domain to produce calcium‐regulated adenosine nucleotide transport activity. By and large, the regulatory domain and the carrier domain function the same way as their closest relatives, and it is the addition of linker domain with the amphipathic α‐helix that has allowed self‐regulation. This type of ‘self‐sequestration’, where the target peptide is part of the same polypeptide chain, is not uncommon in EF‐hand containing proteins. For example, the protein calcyphosin shares domain organisation with the regulatory domain of APC The fusion of two proteins by recombination is a faster mechanism for producing protein with new functionality than The authors declare no conflict of interests.


Bifidobacterium infantis and Gluten Friendly FlourTM; the proposed approach relies upon milk fermentation through the classical starter of yogurt (Lactobacillus delbrueckii subsp. bulgaricus and Streptococcus thermophilus) to avoid a strong production of acetic acid by bifidobacterial and inoculum of B. infantis after the fermentation. The research was divided in 3 steps. The aim of the first step was the optimization of fermentation kinetic by L. delbureckii and S. thermophilus, by combining the amount of flour (either Gluten Friendly Flour-GF- or Control Flour-CF) in milk, temperature and inoculum level; the factors were combined through a mixture design. As a result of this step, the best combination was pointed out: flour at 2.5 g/l; L. delbrueckii subsp. bulgaricus at 6 log cfu/ml; temperature at 37–40°C. The goal of the second step was to study the effect of flour (2.5 g/l) on the viability of B. infantis. GF prolonged the viability of the probiotic for 14 days. In the last step, a synbiotic yogurt, supplemented with GF and fermented with L. delbureckii and S. thermophilus, and then inoculated with B. infantis, was produced. The product was stored at 8 and 15°C. A positive effect of GF was found at 15°C, with B. infantis at 7.0 log cfu/g in GF sample and 5.5.5.7 log cfu/g in CF sample.The main goal of this paper was to design a synbiotic yogurt containing  Nowadays consumers believe that foods can significantly contribute to their health and wellness , or be added as starter cultures to ferment milk base (starter probiotics) , since the adequate fermentation in milk rarely occurs by probiotics alone.The most popular way is to add the probiotic microorganisms together with adjunct lactic starter cultures (PCT/IB2013/000797) for grain seeds to reduce the immunogenicity of gluten in vitro; this approach is based on the use of microwave on hydrated wheat kernels. Microwaves induce structural modifications to endosperm content, and as a result, the immunogenicity is significantly reduced  evaluation of the effects of Gluten Friendly flour on the acidification kinetics of the starter strains; (ii) study of the effects of flour on the viability of B. infantis; (iii) validation at laboratory level and production of a yogurt, supplemented with both flour and B. infantis.The aim of this research was to design a yogurt, fermented by Bifidobacterium infantis Bb02 was purchased from Chr. Hansen ; the strain was grown in MRS broth  supplemented with 0.5% cysteine  at 37°C for 24 h under anaerobic conditions. Lactobacillus delbrueckii subsp. bulgaricus DSM 20081 was purchased from the German Collection of Microorganisms  while Streptococcus thermophilus was purchased from Clerici-Sacco Group . L. bulgaricus and S. thermophilus were grown in MRS broth . Before each experiment the strains were centrifuged at 4,000 g for 10 min and suspended in sterile distilled water (9 log cfu/ml).TM method is an innovative approach to treat wheat grains. Wheat grains was dampened until reaching 15–18% humidity, and then heated through microwaves ; microwave heating was followed by a slow evaporation of the water. This combination (heating/evaporation) was repeated until reaching a final temperature of 80–90°C, and a moisture degree of 13–13.5%. After the treatment, the kernels were cooled and dried at 24°C for 12–24 h. A flour not treated with microwaves was used as control (CF).Gluten Friendly Flour (GF)  was used. Before each experiment, lactobacilli, lactococci and spoiling microorganisms  were checked if they were below the detection limit (standard plate count).L. bulgaricus and S. thermophilus were inoculated to 4, 6, and 8 log cfu/ml, depending on the experimental plan, in 15 ml pasteurized milk supplemented with either GF or CF (0.0–2.5–5.0 g/l); the samples were incubated at 30–45°C for 72 h and the pH was measured after 4, 6, 15, 18, 21, 24, 28, 30, 39, 48, and 72 h. Flour, inoculum and temperature were combined through a simplex centroid. The combinations of the design are in L. bulgaricus+GF; (b) L. bulgaricus+CF; (c) S. thermophilus+GF; (d) S. thermophilus+CF.Four different designs were run: (a) The experiments were performed on two different samples; for each sample the measurements were repeated twice. The results were modeled as acidification (ΔpH) through the lag-exponential model  * exp (–dmaxt)}ΔpH = Δwhere:max is the maximal acidification rate (1/h); ΔpHmax is the maximum level of acidification.α is the time before the beginning of the acidification kinetic (h); dmax and α were analyzed through the theory of the Design of the Experiments, to assess the significant effect of temperature, inoculum and flour as well as of their interactions. The analysis was done through the software Statistica for Windows . The significance of the whole approach, as well as of each variable, was evaluated through the adjusted regression coefficients, the mean square residual, and the Fisher test (P < 0.05). The effect of each factor of the design  was also evaluated through the individual desirability functions, estimated as follows:Then, ΔpHmin and ymax are the minimum and maximum values of the dependent variable, respectively.Where ymax and α and 1 for their maximal values). It is a mathematical function estimated by focusing on the effect of each factor per time, while the other variables/factors of the design were set to a constant value. For this research, the desirability profiles were built by setting the variables to the coded level 0.33 .The desirability is a dimensionless parameter ranging from 0 to 1; it i the answer to the question: how much desired is a result? Generally, desirability is set to 0 for the lowest or the worst value of the dependent variable and 1 for the maximum or the most desired value  to study the effect of each variable, without the influence of possible interactive or synergistic effects; (b) to compare variables or parameters with different units.B. infantis to 7.70 log cfu/ml. The samples were stored at 4 and 37°C and analyzed after 1, 2, 4, 9, 14, and 21 days by pour plating .Saline solution was supplemented with either GF or CF (2.5 g/l) and inoculated with B. infantis was used as control. The experiments were performed twice on two independent samples.Saline solution without flour but inoculated with L. delbrueckii subsp. bulgaricus (6 log cfu/ml) and S. thermophilus (6 log cfu/ml) and incubated at 40°C and let to ferment until a pH 4.0 was attained.Three different productions of yogurt were prepared as follows: milk supplemented with Gluten Friendly flour (2.5 g/l) (GF), control flour (2.5 g/l) (CF) or without flour . Then, the three batches were inoculated with B. infantis (6.5–6.8 log cfu/ml), divided in samples of 25–30 g in sterile 50 ml-tubes and stored at 8 and 15°C. Immediately after the inoculation of bifidobacteria and after 3, 7, 10, 14, and 17 days microbiological and chemico-physical analyses were done.After the fermentation, the batches were inoculated with Neomycin-Nalidixic acid-Lithium chloride-Paromomycine: 2 g/l neomycin sulphate, 4 g/lparomomycine sulphate, 0.3 g/l nalidixic acid, and 60 g/l lithium chloride; all reagents were purchased from Sigma-Aldrich), incubated at 37°C for 48–72 h for bifidobacteria; Slanetz/Bartley Agar incubated at 37°C for 48 h, for enterococci; Plate Count Agar (PCA) incubated at 5 C for a week or 32°C for 48 h for psychrotrophic bacteria and mesophilic bacteria, respectively; Baird-Parker agar base, with egg yolk tellurite emulsion, incubated at 37°C for 48 h for staphylococci and Micrococcaceae; Pseudomonas Agar Base (PAB) with CFC Selective Supplement incubated at 25°C for 48 h for Pseudomonas spp.; Violet Red Bile Glucose Agar (VRBGA), incubated at 37°C for 24 h for Enterobacteriaceae; Violet Red Bile Agar (VRBA) incubated at 37°C or 42°C for 18–24 h for total and fecal coliforms, respectively; Sabouraud dextrose agar, supplemented with chloramphenicol (0.1 g/l) , incubated at 25°C for 48 h or 5 days, for yeasts and molds, respectively. All the media and the supplements were from Oxoid.For microbiological analyses, the following media were used: MRS Agar and M17 Agar+lactose, incubated at 30°C or 44°C for 48–72 h for mesophilic and thermophilic lactobacilli and lactococci; MRSAgar+cysteine+NNLP antibiotic solution . Color was evaluated by a colorimeter Chroma Meter  by measuring CIE L* (lightness), a* (redness), and b* (yellowness) values.pH was measured by a pH-meter and aBifidobacterium were analyzed by a multifactorial analysis of variance and Tukey's test as the post-hoc comparison test. Storage time, temperature and kind of samples  were used as categorical predictors; the critical P-level was set to 0.05.The experiments were repeated twice on two independent samples. The results of L. delbrueckii subsp. bulgaricus and S. thermophilus. The microorganisms experienced a sigmoid-like acidification (see as an example The aim of the first step was to study the effect of either GF or CF on acidification kinetics max (acidification), and α (time before the beginning of acidification kinetic) for L. bulgaricus and S. thermophilus. ΔpHmax was 2.5–3.0 for L. bulgaricus and 1.8–2.7 for S. thermophilus. This microorganism did not experience an acidification kinetic in the combination C. The parameter α was never found for S. thermophilus, while it was from 0 (combination A) to 14 h (combination B) for L. bulgaricus.max and α were used as inputs to run a DoE analysis and to study the effect of flour, inoculum and temperature. The significance of these effects is in L. bulgaricus, as shown by the high regression coefficients for both GF and CF (from 0.947 to 0.961).ΔpHmax) was affected by all factors as individual terms and by the interactions “inoculum/flour” and “temperature/flour,” but the most significant term was the individual effect of flour. The parameter α was affected by the individual terms of temperature and flour and by the interactive factors “inoculum/flour” and “temperature/flour.” On the other hand, the significance of the approach was lower for S. thermophilus.The statistical weight of the variables was the same for both GF and CF; acidification  in a 2D space. max with GF (A) and CF (B). The effects were similar, and the model predicted the maximum level of acidification (ΔpH 3) with flour at coded levels 0.5–1.0  and inoculum at 0.25–0.50 ; the effect of temperature was negative, as an increase caused a decrease of ΔpHmax.A table of standardized effect offers a qualitative output; some details on the quantitative correlation of the factors with ΔpHThe triangular plots for α are in max are in Ternary plots suffer a main drawback: they offer quantitative trends for interactions, but it is not possible to evaluate the effect of each factor alone. This goal can be achieved through the desirability profiles. The desirability profiles of the individual effects of inoculum, flour, and temperature on ΔpHThe same approach was used for the lag phase . DesirabS. thermophilus, too . However, the results of the DoE approach highlighted an uncoupling between the level of acidification and the lag phase: the combinations resulting in the highest level of acidification caused a significant prolongation of the lag phase. Therefore, a different goal was chosen: acidification of 2.0–2.5 with a lag phase of 6–7 h. The combination of all desirability profiles (saddle point approach) suggest that this goal could be achieved by setting the variables as follows:The last step of the statistical modeling was the optimization, i.e., the choice of the best combinations of the variables. For this research, the best combination would ideally result in the highest level of ΔpHflour at 2.5 g/lL. delbrueckii subsp. bulgaricus at 6 log cfu/mlTemperature at 37–40°CB. infantis. The results are in Before producing the synbiotic yogurt, the effect of flour was studied on B. infantis. The level of mesophilic and termophilic lactobacilli and lactococci was always higher than 6 logcfu/g, while enterobacteria, pseudomonads, yeasts and staphylococci were below the detection limit (data not shown).The synbiotic yogurt was produced through the classical starter strains and then supplemented with B. infantis was analyzed through a multifactorial ANOVA; the results are in B. infantis was affected by time, temperature, and flour (The viable count of nd flour .Bifidobacterium has 3 outputs: correlation storage time vs. viable count (8A); qualitative correlation kind of flour vs. viable count (8B); actual data (8C). The decomposition of the statistical hypothesis, does not show effective or actual trends but it is a mathematical extrapolation of their statistical effect.A second output of multifactorial ANOVA is the decomposition of the statistical hypothesis, which shows the correlation of each factor or interactive term with the dependent variable. The decomposition of the statistical hypothesis for the viable count of B. infantis, as the cell number decreased within storage. B. infantis was 7.0 log cfu/g in GF sample and 5.5–5.7 log cfu/g in the control and in CF sample.pH (3.8–4.0), Aw (0.98) and color did not undergo significant changes (data not shown).The decomposition of the statistical hypothesis for the interaction time/temperature/treatment shows when GF acted . The posB. infantis and GF flour) involves different microorganisms.The optimization of a product is a complex process, as many variables could play a significant role and affect the final output; in this paper, the optimization of synbiotic yogurt was done through a step-by-step approach as the proposed product , and α, to highlight possible delays in the kinetic or a reversible inhibition.First, the effect of GF on the acidification kinetics was studied, as the main requirement of an ingredient is that it must not delay or significantly affect the performances of a starter culture . Namely, flour positively acted on acidification and this result was different from what found on L. acidophilus, which experienced a positive trend up to 2.5 g/l  and the parameter α. The combinations resulting in the highest reduction of pH also caused a delay of the kinetic. To the best of our knowledge, this trend was never found on L. bulgaricus and S. thermophilus and represents a challenge, as it was not possible to find out a combination with the highest acidification and the lowest value of α. The lack of adequate acidification could lead to long fermentation times with unsuitable economic and hygienic consequences .In the validation in synbiotic yogurt, the inoculum was lower (6.5–6.8 log cfu/g) as preliminary reports suggested that in complex systems GF could promote or enhance growth; thus, a compromise between the viable count required for a viability test (7–8 log cfu/g) and a growth assay (4–5 log cfu/g) was chosen. Therefore, this step, as previously reported, was not aimed at defining the shelf life but at studying the effect of GF in a complex system. Further investigations are required to define shelf life by adding to the yogurt higher concentration of B. infantis. However, the design of this synbiotic yogurt should be completed with the optimization of the inoculum of B. infantis after the fermentation to fulfill the basic requirements of law (probiotic at least 7 log cfu/g for the entire storage time).In addition, the results of 2nd and 3rd step both suggest that the supplementation of GFF at 2.5 g/l in a yogurt is a good compromise between technological performances of starter cultures and prolongation/enhancement of the viability of the probiotic microorganism Bifidobacterium. The most important findings can be summarized as follows:This paper proposes a DoE approach to produce a traditional yogurt supplemented with GF and a probiotic The flour is responsible on an uncoupling on the fermentation kinetics of the starter microorganisms of the yogurt (increase of acidification and induction of a delay in the kinetic). Thus, it is not advisable to use flour amounts > 2.5 g/l.B. infantis.The supplementation of GF exerted a positive effect in a simple system, as it prolonged the viability of L. delbrueckii subsp. bulgaricus and S. thermophilus and supplemented with B. infantis and a prebiotic-like compound (GF). GF was able to cause an increase of bifidobacteria in the last days of storage.It is possible produce a synbiotic yogurt, fermented with In conclusion, this paper suggests a way to produce a synbiotic yogurt containing bifidobacterial and GF; the combination of these two factors could prolong and enhance the viability of the probiotic. The protocol hereby proposed also shows a way to counteract the drawback of bifidus pathway (production of acetic acid), by using the traditional starter cultures of yogurt. The combination of all these data suggests that the approach proposed in this paper is a promising way; however, further efforts are required to translate these preliminary data in an effective protocol to produce a new functional food. Some requirements have to be fulfilled: the definition of a unique death kinetic of the probiotic, along with a focus on the mode of action of GF, in order to evaluate and define a commercial shelf life as requested by the Regulatory Agencies.AB, MS, CL, and MC conceived the study. AB, BS, DC, and MC designed the experiments. CL prepared the GF. BS, and DC performed the experiments. AB performed the statistic and wrote the paper. CL funded the research. All authors reviewed the paper.CL is the inventor of the following patents “Method for the detoxification of gluten proteins from grains of cereals. Patent Cooperation Treaty PCT/IB2013/000797” and “Methods for the detoxification of gluten proteins from grains of cereals and related medical uses. Italian priority patent n° 102015000084813 filed on 17.12.15.” The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We acknowledge their adoption of a more commonly used definition on the relative contribution. In this correspondence, we confirm the validity of the major conclusions of Z15 and compare the definitions and calculations of the relative contributions between Z15 and G17. We also identify an important research gap on the most appropriate estimation of the relative contributions of climate and land cover to the annual water yield using these global theoretic frameworks , which require further attention.We appreciate the comments on the relative contributions of climate and watershed condition to water yield by Gudmundsson et al.ψ = P/PET = 1 and m = 2) and their corresponding hydrological sensitivities and concluded that changes in land cover in watersheds with ψ < 1 or m < 2 can lead to greater hydrological alterations. In addition, Z15 applied those results to estimate the relative contributions of ψ and m to R/P, which pertain to an application aspect of the key conclusions.Z15 first validated the broad application of the Fuh framework Eqs.  using puG17 questioned the calculation of the relative contributions of Z15. It is critical to stress that such questioning was only on the application aspect of Z15 rather than on their central conclusions. However, the title of G17 has led to significant confusion and a misunderstanding of Z15 as well as of global theoretical frameworks  in scientific communities. Thus, we further confirm that the central conclusions of Z15 were not questioned by G17.ψ is defined as the wetness index , whereaentclass1pt{minimaψ and m to R/P. The relative contributions can be defined in various ways depending on the research objectives. Z15 defined them as the relative contributions of ψ and m to the sensitivities of R/P  to ϕ (PET/P) , whereas the latter is relative to the climate with regard to dryness (PET/P). Therefore, it is no surprise that they have different trends.The central debate between Z15 and G17 lies in the relative contributions of R/P (Eq. ), aimingϕ is rearranged to ψ  to ϕ (PET/P). The same phenomenon is also found for C*mϕ and C*mψ. Therefore, Figs. To further demonstrate the physical consistency of Z15, Eqs.  and 4)  4) can bsee Eqs. –10) for forϕ is R/P to ψ (Sψ) and m (Sm) can be derived from Eq. (The sensitivities of from Eq.  as:8\docR/P to ϕ (Sϕ) and m (S*m) can be derived from Eq. (The sensitivities of from Eq.  as:10\do