Vestibular-evoked myogenic potential triggered by galvanic vestibular stimulation  evaluates the motor spinal cord and identifies subclinical myelopathies. We used galvanic-VEMP to compare spinal cord function in individuals infected with human T-cell lymphotropic virus type 1 (HTLV-1) from asymptomatic status to HTLV-1-associated myelopathy (HAM).This cross-sectional study with 122 individuals included 26 HTLV-1-asymptomatic carriers, 26 individuals with possible HAM, 25 individuals with HAM, and 45 HTLV-1-seronegative individuals (controls). The groups were similar regarding gender, age, and height. Galvanic stimuli  were applied bilaterally to the mastoid processes and VEMP was recorded from the gastrocnemius muscle. The electromyographic parameters investigated were the latency and amplitude of the short-latency (SL) and medium-latency (ML) responses. While SL and ML amplitudes were similar between groups, SL and ML latencies were delayed in the HTLV-1 groups compared to the control group (p<0.001). Using neurological examination as the gold standard, ROC curve showed an area under the curve of 0.83 (p<0.001) for SL and 0.86 (p<0.001) for ML to detect spinal cord injury. Sensibility and specificity were, respectively, 76% and 86% for SL and 79% and 85% for ML. Galvanic-VEMP disclosed alterations that were progressive in HTLV-1-neurological disease, ranging from SL delayed latency in HTLV-1-asymptomatic carriers, SL and ML delayed latency in possible HAM group, to absence of VEMP response in HAM group.The worse the galvanic-VEMP response, the more severe the myelopathy. Galvanic-VEMP alteration followed a pattern of alteration and may be a prognostic marker of progression from HTLV-1-asymptomatic carrier to HAM. Human T-cell lymphotropic virus type 1 (HTLV-1)-associated myelopathy (HAM) is a chronic inflammatory disease that occurs in approximately 3% of HTLV-1-infected individuals . HAM affThe diagnosis of HAM is based on clinical and imaging methods ,8. DurinGalvanic vestibular stimulation (GVS) applied to the mastoid bone triggers a motor response in posture-controlling muscles . The eleBipolar and bilateral GVS is applied to the mastoid bones using a cathode on one side and an anode on the contralateral side . The galThe aim of the present study was to use galvanic-VEMP to compare spinal cord function of HTLV-1-infected individuals in different levels of spinal damage that ranged from asymptomatic carrier to HAM.For this cross-sectional comparative study, galvanic-VEMP was recorded from the lower limb of HTLV-1-asymptomatic carriers, individuals with possible HAM, individuals with HAM, and non-infected healthy individuals (controls).Declaration of Helsinki and it was approved by the Research Ethics Committee of the Federal University of Minas Gerais under number 266 and the Research Ethics Committee of the Hemominas Foundation under number 131. All participants provided voluntary written consent and declared that they were aware of the study procedures and their freedom to participate.This research was conducted in accordance with the principles expressed in The sample size was calculated using G*Power software 3.1.9.2  to achieve a power of 80% and significance level of 5% based on the mean and standard deviation of the SL response of patients with HAM and healthy controls . The finThe participants in this study were recruited from a cohort of former blood donors infected with HTLV-1 who have been followed by the Interdisciplinary HTLV Research Group (GIPH), since 1997, in Belo Horizonte, Minas Gerais State, Brazil , 28. TheThis present study was a transversal evaluation of 122 participants of the GIPH cohort. They were selected when they attended to the follow-up medical appointment scheduled by the GIPH and 160 individuals were invited to participate from February 2014 to June 2016. Twenty participants of the cohort refused to participate and 18 were excluded because of syphilis (n = 1), human immunodeficiency virus type 1 , hepatitis B or C (n = 3), recurrent episodes of vertigo (n = 2), diagnosis of peripheral vestibular disease (n = 3), and inability to remain in a standing position (n = 7).This study was composed by the controls [G1 (n = 45)], that were the HTLV-1-seronegative blood donors as assessed by enzyme-linked immune sorbent assay (ELISA)] and by the group of HTLV-1-infected participants (n = 77), that was the HTLV-1-seropositive blood donors as assessed by ELISA and confirmed by Western blot analysis  or by real-time polymerase chain reaction (PCR)] .The HTLV-1 group was further divided into three subgroups according to neurological assessment. The HTLV-1-asymptomatic group [G2 (n = 26)] consisted of individuals without clinical symptoms according to Castro-Costa et al. criteria  30] and and30] aThe participants were submitted to a clinical interview and neurological examination followed by galvanic-VEMP testing with the response recorded from the lower limb. Each participant was submitted to all the evaluations at the same day in the reference hospital of the Faculty of Medicine from UFMG, in Belo Horizonte, Minas Gerais State, Brazil. The evaluations were conducted by the same physicians, a specialist in infectious diseases, neuro-otologist and a neurologist.The clinical interview considered the demographic variables , the medications in use, the complaint of dizziness, walking difficulties, history of vestibular disease and of stroke.The neurological examination included the abdominal cutaneous, patellar tendons, and Achilles tendon reflexes, cranial nerves, sensitivity, muscle strength, gait, coordination, and abnormal movements. EDSS  and OMDSThe GVS was applied on the mastoid bone and the VEMP response recorded from the lower limb. The GVS was characterized as a direct, monophasic, and rectangular current with an intensity of 2 mA and a duration of 400 ms . The bipolar current was applied on the mastoid processes using self-adhesive, circular surface electrodes . For transmastoid binaural stimulation, the two current polarity settings used were cathode left and anode right (CLAR) and cathode right and anode left (CRAL). The stimulation polarity was controlled via a computer. For each test, four sets of 30 stimuli were applied and distributed, resulting in 30 responses recorded from the left lower limb (15 CLAR and 15 CRAL stimuli) and 30 responses recorded from the right lower limb (15 CLAR and 15 CRAL stimuli). This procedure was repeated for each leg to ensure data replication.During the procedure, the subjects stood barefoot on a flat surface with their eyes closed, feet close together, and bodies leaning forward to contract the gastrocnemius muscle ,18,19. TThe EMG response triggered by GVS was measured using self-adhesive electrodes . A pair of recording electrodes was vertically placed 5 cm below the popliteal fossa on the medial head of the gastrocnemius muscle at approximately 5 cm between their centers. A reference electrode was placed on the back of the thigh at approximately 10 cm above the superior most recording electrode recording electrodes. The galvanic-VEMP was first measured in the left leg and then in the right leg. The tests were performed with a 2-min resting interval to avoid muscle fatigue .dx.doi.org/10.17504/protocols.io.nxbdfin.The EMG signals were measured, corrected, filtered between 10 Hz and 1 kHz, and digitized at a sampling frequency of 5 kHz. Data were collected for 500 ms, starting 100 ms before GVS. EMG responses to 15 consecutive stimuli associated with each polarity configuration  were averaged to produce final traces. The galvanic-VEMP protocol is available at Two independent examiners performed blind analyses of galvanic-VEMP traces. The traces were analyzed for the onset (in ms) of SL and ML responses as well as the amplitude (in μV) of SL (SL-amp) and ML (ML-amp) waves. Following the superimposition of traces with inverted polarity , the point where the traces diverged from the EMG baseline, which marked SL and ML onset, could be visualized and measured by a cursor. The first trace divergence, which occurred at approximately 50 ms, marked the onset of the SL response. Following this, the traces returned to baseline and then diverged again. The second trace divergence, which occurred at approximately 100 ms, marked the onset of the ML response . The ampData were analyzed using EpiData 3.0  and SPSS 15.0  software. The Shapiro-Wilk test was used to analyze the asymmetric distributions of all continuous variables. Among them, the age showed a normal distribution, so that it was presented as media (± standard deviation); the height, SL onset, ML onset, SL-amp, and ML-amp showed non-normal distribution, so that they were presented as median (Quartil Q1/Quartil Q3).To assess possible confounding variables, a multiple linear regression analysis by backward elimination was performed. The independent variables were height, age, sex, and group. The dependent variables were SL onset, ML onset, SL-amp, and ML-amp.The Spearman correlation coefficient was calculated to measure the concordance degree between the two independent examiners. The correlation was classified as weak (r = 0–0.40), moderate (r = 0.41–0.70), or strong (r = 0.71–1).To determine whether the galvanic-VEMP response was normal or altered, we constructed the receiver operating characteristic (ROC) curves and established SL and ML cut-off values based on sensitivity and specificity analyses. Neurological examination  were considered as the gold standard.Between-group comparisons of continuous variables were performed using a Kruskal-Wallis test with Bonferroni correction. Between-group comparisons of categorical variables were performed using a Chi-square or Fisher’s exact test. A significance level was defined as 5%.The uninfected control group (G1) consisted of 45 HTLV-1-seronegative subjects. The HTLV-1-seropositive group (n = 77) was divided into three subgroups, including 26 asymptomatic individuals (G2), 26 individuals with possible HAM (G3), and 25 individuals with HAM (G4).The general characteristics of the participants are shown in According to multivariate analysis, the potential confounders age, sex, height, and weight did not influence the variables of interest. The results indicated that the group type was associated with changes in SL  and ML  responses.The blind analyses of galvanic-VEMP traces performed by the two examiners were strongly correlated for SL  and ML  and moderately correlated for SL-amp  and ML-amp .For each group, there was no significant difference between the EMG responses of the right and left legs (p>0.05). Thus, the group comparisons were performed using SL and ML measurements from either the right or left leg. To increase the sensitivity of the analysis, for all participants, we analyzed the measurements taken from the leg presenting higher latencies.The latency and amplitude of SL and ML responses are shown in SL responses were significantly delayed in the HTLV-1-asymptomatic, possible HAM, and HAM groups compared to the control group SL response. ML responses were longer in the possible HAM and HAM groups compared to those of the HTLV-1-asymptomatic and control groups. The longest latencies were found in patients with the most severe neurological impairment.There was a significant correlation between EDSS and ML responses in possible HAM and HAM groups, showing that there was a parallel between the clinical profile  and ML latencies. The correlation between EDSS and ML was strong (p<0.001 and r = 0.707) and between OMDS and ML was moderate (p<0.001 and r = 0.642) .We classified the galvanic-VEMP response as normal or altered. An altered galvanic-VEMP response occurred when the SL or the ML wave from at least one leg was delayed or absent. Using neurological examination as the gold standard, we constructed the receiver operating characteristic (ROC) curves to evaluate delayed SL and ML latencies. SL and ML responses presented good areas under the curve AUC; .The best cut-off values for SL and ML responses were 64 ms  and 122 ms , respectively. To determine if the SL or ML response from at least one leg was absent, the galvanic-VEMP was performed twice. When SL or ML responses were absent, the galvanic-VEMP was repeated three times. In the HTLV-1-asymptomatic group, the most frequent type of altered response was SL delayed latency . In the In the present study, galvanic-VEMP disclosed an altered EMG response of the inferior limb in HTLV-1-infected individuals that otherwise were considered asymptomatic carrier. For the SL and ML components of the EMG wave, a greater latency delay was associated with a greater motor impairment.VEMP triggered by acoustic stimulation has been used to evaluate the brainstem and cervical spine ,34, inclIn s = -0.57; p<0.01)  for categorical variables.(PDF)Click here for additional data file.S3 TableData are expressed as absolute number (percentage); n, number of participants with performed both VEMP recorded from the lower limb muscle and VEMP recorded from the cervical muscle.(PDF)Click here for additional data file.S1 Figversus galvanic-VEMP medium-latency response, (B) OMDS values versus galvanic-VEMP medium-latency response.(A) EDSS values  ML, medium-latency response; EDSS, Expanded Disability Status Scale; OMDS, Osame’s Motor Disability Score; p, probability of significance; r, Spearman correlation coefficient.(TIF)Click here for additional data file.


The need for home healthcare programs is an increasingly becoming important common component of healthcare worldwide, as an alternative to hospitalization, owing to the growing elderly population, chronic and acute diseases that need continuous monitoring and care. The overall aim of this study was to describe and assess the quality of life (QOL) and associated determinants among patients enrolled in the Home Health Care (HHC) program affiliated with the Ministry of National Guard Health Affairs in Riyadh, Saudi Arabia.This cross-sectional study was conducted among patients enrolled at the HHC program. The World Health Organization QOL questionnaire (WHOQOL-BREF) was used to collect data about the different domains of patients’ QOL. Logistic regression models were fitted to determine factors associated with QOL low score.. The overall QOL for HHC patients was significantly affected by both socio-demographic and morbid characteristics. In the final Multivariate logistic regression models, marital status, and having psychological problems, stroke and number illness were independently associated with the overall QOL of HHC patients . The physical health domain score was significantly associated with education level, having psychological problems and stroke  whereas the psychological domain score was significantly associated with age (p = < 0.001) and three types of chronic diseases: pulmonary (p = .002), psychological problems (p = < 0.001). The social domain score was significantly associated only with the marital status (p = .026). The environmental domain was significantly associated with the education level and having stroke (p = .017 vs .027).The study included 253 patients. Mean age was 67.05 (± 20.0)The overall QOL and its domains are significantly associated with several different factors. Many of these factors can be monitored and enhanced by improving quality of HHC services, thus improving the QOL of patients. Home Health Care (HHC) consists of healthcare services that are provided to patients in their homes by qualified healthcare providers under the supervision of a physician. The purpose of these home healthcare services is to help improve all aspects of the quality of life (QOL) of patients, support their independence, and increase their level of well-being . GloballThe World Health Organization (WHO) defines QOL as an individual perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concerns . QOL is The majority of previous studies have focused on assessing a patient’s QOL within hospital settings rather than outside settings like HHC . A studyResearchers have started to study and assess different aspects of HHC on QOL. For example, in Sweden they tried assessing the effect of patient-centered HHC services on the QOL of elderly patients. The results showed that more patient involvement in HHC plans and decisions improve their satisfaction and ultimately improve their QOL . AnotherIn Saudi Arabia, all the current HHC programs are public funded programs. The first HHC program was established in 1991 by the King Faisal Specialized Hospital, and was only for terminal cancer patients. Later in 1995, the Ministry of National Guard Health Affairs established its HHC program to provide home healthcare services to minimize the length of hospital stay. In 2008, the Saudi Ministry of Health started introducing the national HHC program . This naThis study is a cross-sectional study, using the Arabic version of WHOQOL-BREF. The study was conducted within the HHC program of National Guard Health Affairs in King Abdul-Aziz Medical City in Riyadh.All patients enrolled in the HHC program who were available during the home visit and willing to participate in the study survey were included. The entire population of 300 patients enrolled in HHC program was surveyed. We recruited the study participants by visiting them at their home and conduct a face-to-face interview by well-trained social worker who is familiar with and working at HHC program of Ministry National Guard Health Affairs.Data were collected using the WHOQOL-BREF questionnaire Arabic version for measuring QOL . It is op < 0.05 was considered significant. Missing data were imputed using the multiple imputation technique [All gathered data were entered into a computer using IBMSPSS . Collected data were checked and cleaned to remove any entry errors. Data were summarized using descriptive statistics such as percentage and mean (±SD) and compared using inferential statistics such as the t-test and chi-square; as appropriate. For each domain the mean score was calculated by dividing the total score of all items in the domain by the number of items in the domain. Then the overall mean score had been calculated by adding up the mean score for each domain divided by number of the domains. For the purpose of regression analysis, subjects were divided into a high-score group and low-score group based on the median value as cut of point of the total WHOQOL-BREF score and four domain scores as done in similar published studies , 18. Surechnique ., 08.7% had pulmonary disease, and 26.9% had stroke.The respondents’ characteristics are shown in Table The QOL domains scores (mean and standard deviation) are shown in Table p = 0.002), Employment status (p = 0.019) hypertension (p = 0.040), and having psychological problems (p < 0.001) and stroke (p = 0.003). However, in the physical domain, education level, employment status, housing type, and having cancer psychological problems and stroke differed significantly in the two groups. Regarding the psychological domain, significant differences were observed in age, education level, marital status, and having hypertension pulmonary disease, psychological problems and stroke. In the social relationships domain, the only significant differences were related to marital status, and having psychological problems. As for the environmental domain, there was significant difference in age, education level, employment status, housing type, and having diabetes and stroke see the details in the additional file 1).The overall QOL score differed significantly in the two groups in terms of marital status , psychological problems  and stroke  while the number of illnesses has a borderline significance on overall QOL . However, in the physical domain significant factors were education, psychological problems, and stroke. Whereas in the psychological domain significant factors were age, and having psychological problems, pulmonary disease and stroke). In the social relationships domain, the only one significant factor was marital status. In the environmental domain, the significant factors were education, and having stroke, Table In logistic regression analysis factors significantly associated with overall score of QOL for HHC patients were marital status  of HHC patients. We conclude that QOL domains are affected by many different factors, and our results show that some factors affect more than one domain . Dealing with those factors and understanding their effect on QOL is a shared responsibility of healthcare providers, HHC program planner s and family caregivers; many of these factors can be monitored and enhanced by improving the quality of HHC services and thus improve the QOL of patients. The National Guard HHC program can be improved to provide high-quality services by well-trained teams.Our findings suggest that there are opportunities for improvement initiatives for quality of life among HHC patients. The priority of such initiatives should focus on the psychological well-being, especially patients with stroke. It’s also worth mentioning that although the quality of social relationships of HHC patients seems relatively good, showing that the local social culture accept patient to live as valuable member of the family and deserves family’s members support, this social culture should be maintained and encouraged by healthcare providers and those in charge of HHC program. Moreover, quality of life among HHC patients could be improved by enhancing the communication skills of HHC providers with care recipients and family caregivers; this could foster both physical and psychological health aspects as well as prompting the self-determination and person-centered care thinking among HHC patients, which requires involving them in HHC plans and decisions as strategy to improve patients satisfaction and ultimately their QOL . Future


Staphylococcus aureus in a tertiary hospital of northwest China from 2010 to 2016. Trends were analysed by linear regression, and correlations were assessed by an autoregressive integrated moving average model. The total consumption of antibiotics halved during the 7-year study period, while the rates of resistance of S. aureus decreased significantly or remained stable; methicillin-resistant S. aureus (MRSA) declined markedly, from 73.3% at the beginning of the study to 41.4% by the end. This latter decrease was significantly correlated with the consumption of several classes of antibiotics. In conclusion, reduction in antibiotic use impacted significantly on resistance rates and contributed to a decline in MRSA prevalence.The overuse of antibiotics and the rapid emergence of antibiotic resistance prompted the launch of an antimicrobial stewardship programme in 2011. This study aimed to investigate the trends and correlations between antibiotic consumption and resistance of  Antibiotic resistance is a serious threat to public health . InfectiIn response to a WHO programme in 2011  to stem Staphylococcus aureus, and particularly methicillin-resistant strains (MRSA), in this hospital over the period 2010–2016.In July 2011, several antimicrobial control regulations were introduced in the First Affiliated Hospital of Xi'an Jiaotong University (FAHXJU). This study reports the trends in, and correlations between, antibiotic consumption and resistance of FAHXJU is a 2541-bed tertiary-care teaching hospital located in the northwest of China. Antibiotic susceptibility patterns of inpatient isolates were monitored by the Clinical Microbiology Laboratory and antibiotic usage was obtained from the computerised database of the Department of Pharmacy. The data were collected per quarter from 2010 to 2016. The need for an informed consent was waived by the ethics review board.In brief, the national rectification scheme introduced in April 2011 , restricS. aureus-positive clinical specimens from inpatients were included in the database. The isolates were classed as susceptible, intermediate susceptible or resistant, according to Clinical and Laboratory Standards Institute criteria [Identification and susceptibility testing of bacterial isolates were performed using the automated VITEK 2 automated system . All criteria . Duplicap’ and ‘q’ of the ARIMA  model with autocorrelation and partial autocorrelation. Subsequently, model parameters were estimated by the Maximum Likelihood method and finally checked for adequacy of the model. Independent variables with P < 0.05 in the univariate ARIMA models were included in multivariate ARIMA regression model. All reported P values were two-sided, and P < 0.05 were considered statistically significant.The trends in antibiotic resistance, antibiotic consumption and medical quality indicator data were analysed by linear regression with SPSS version 19.0. Correlations between antibiotic consumption and antibiotic resistance were analysed by autoregressive integrated moving average (ARIMA) models, allowing for possible lag times of a half year , 12. We β = 8.411, P < 0.05) and values increased by 74.19%. The average number of hospital stays decreased significantly  by 30.6%, as did the mortality rate . Likewise, significant reductions were also recorded for the incidence of nosocomial infections , and antibiotic usage .Administrative data were obtained regarding the number of hospitalisations, hospital stays and other medical quality indicators over the study period . The numS. aureus isolates were collected: 447 isolates in 2010, 732 in 2011, 728 in 2012, 582 in 2013, 382 in 2014, 532 in 2015 and 572 in 2016. P < 0.05, S. aureus. Significant decreases in the consumption of oxacillin, benzylpenicillin, erythromycin, ciprofloxacin, levofloxacin and gentamicin were also noted in contrast to increases in consumption of clindamycin, moxifloxacin, vancomycin and sulfamethoxazole/trimethoprim (P < 0.05). Less substantial changes in the consumption of linezolid were evident. Tetracyclines were not available for prescription in the hospital during the study period.In total, 3975 P < 0.05), respectively (P < 0.05) correlations of resistance and consumption were noted for clindamycin and moxifloxacin in lag quarter 1, and for ciprofloxacin and sulfamethoxazole/trimethoprim after 6 months (lag quarter 2). The only negative correlation was for benzylpenicillin in lag quarter 0 (P = 0.026).Positive correlations were found for resistance to the agent and the consumption of oxacillin and gentamicin in lag quarter 0, with coefficients of 0.334 and 0.017 .The total consumption of antibiotics decreased from 951.88 DDDs/1000 PDs in quarter 1 of 2010 to 346.45 DDDs/1000 PDs in quarter 4 of 2016 (P < 0.05). Meanwhile, the isolation rate of MRSA would rise with increased usage of the total antibiotics in the next quarter . However, in the multivariate ARIMA model  is also noteworthy. However, these agents are not normally used for the treatment of nfection , 25. In nfection . Our finS. aureus. Nevertheless, we believe that this study based on longitudinal data obtained over several years makes a meaningful contribution to our understanding of the relationship between usage of antimicrobials and resistance rates as a consequence of the implementation of the antimicrobial stewardship programme in our tertiary care hospital. Since the end of the study, resistance rates of S. aureus have remained significantly reduced, with a continuous decline in MRSA infections. The mechanisms underlying antibiotic consumption and MRSA resistance are worthy of further study.This study was subject to several limitations. First, it had a single-centre, retrospective, observational design, and used aggregate data with an inherent risk of bias, since data from individual patients might give different results. Secondly, the density of antibiotic use might not accurately reflect the real antibiotic use in adults with renal impairment; however, it is the most commonly applied metric for measuring antibiotic use. Thirdly, we were unable to differentiate infection from colonisation with


Piaractus mesopotamicus was used as a model to evaluate the effect of the antimicrobial florfenicol on the diversity of the gut microbiome as well as antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) using a metagenomic approach.Aquaculture is on the rise worldwide, and the use of antibiotics is fostering higher production intensity. However, recent findings suggest that the use of antibiotics comes at the price of increased antibiotic resistance. Yet, the effect of the oral administration of antibiotics on the mobility of microbial resistance genes in the fish gut is not well understood. In the present study, P. mesopotamicus because of the antibiotic exposure. MGEs co-occurring with ARGs showed a significant positive correlation with the total ARGs found. Furthermore, shifts in the gut microbiome towards well-known putative pathogens such as Salmonella, Plesiomonas, and Citrobacter were observed following florfenicol treatment. Mainly Plesiomonas and Citrobacter harbored genes that code for multidrug and phenicol efflux pumps. Moreover, several genes related to RNA processing and modification, cell motility, SOS response, and extracellular structure were enriched due to the antibiotic application. The observed effects were visible during the complete application phase and disappeared at the post-exposure phase.The total relative abundance of ARGs and MGEs significantly increased during the antibiotic exposure. Additionally, phage integrases, transposases, and transposons flanking ARGs accumulated in the gut microbiome of Our findings suggest that the oral administration of antibiotics increases the potential for MGE-mediated exchange of ARGs in the gut of fish and could contribute to the enrichment and dispersion of ARGs in aquaculture systems. Importantly, this increase in the potential for ARGs exchange could be an effect of changes in community structure and/or ARG mobilization.The online version of this article (10.1186/s40168-019-0632-7) contains supplementary material, which is available to authorized users. The rapid acquisition of genes coding for antibiotic resistance of bacteria is a major health concern. It has been stated that the continuous increase of pathogenic bacteria which are resistant against commonly used antibiotics will induce in 2050 up to 10 million cases of death per year and global costs of 100 trillion USD [Aquaculture poses a potential risk for the dissemination of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) due to the widespread use of antibiotics . The proDiversity and abundance of ARGs and MGEs have been explored in fish feces , fishmeaHowever, the origin and potential spreading of genes that mediate antibiotic resistance in aquaculture is not clear . A studyPiaractus mesopotamicus, a commonly farmed fish in South America. The objectives of the study were (1) to investigate the diversity and abundance of ARGs and MGEs before, during, and after antibiotic exposure, (2) to evaluate the co-occurrence of MGEs and ARGs and (3) to link ARGs to their respective host bacteria.In the frame of this study, we investigated the influence of florfenicol, a broad-spectrum fluorine derivative of chloramphenicol frequently used in aquaculture , on the P. mesopotamicus during a time series experiment of 34 days including pre-exposure phase, exposure phase, and post-exposure phase. The obtained data was compared to control animals, which did not receive antibiotics but were kept under the same conditions. As expected, the body weight of the sampled fish slightly increased over the experimental period from 651.4 ± 107.1 g at day 0 to 766.2 ± 165.8 g at the end of the antibiotic exposure phase and 781.44 ± 171.1 g at the post-exposure phase. An effect of the antibiotic treatment at the end of the exposure phase comparing treated and control animals was not visible  were removed . Clean reads were taxonomically annotated using Kaiju: 25.10–94.02% corresponded to P. mesopotamicus was dominated by the families Bacteroidaceae (45.7%), Porphyromonadaceae (11.2%), Prevotellaceae (5.2%), and Lachnospiraceae (2.9%) in the pre-exposure phase and was comparable to the control animals, which were kept for the entire experimental period without antibiotic. As a result of the antibiotic exposure, Bacteroidaceae were reduced in the gut of the animals, decreasing from 45.7 ± 4.7% at day 0 to 0.02 ± 0.01% at day 7. At the same time, Enterobacteriaceae increased from 0.16 ± 0.05% to 53.19 ± 24.3% . Interestingly, also the abundance of phages increased as a result of the antibiotic treatment, from 0.008 to 0.010%, 0.031%, and 0.220% at days 0, 1, 4, and 7 respectively. Aeromonaphages (0.066%), Pseudomonaphages (0.038%), Vibriophages (0.029%), Escherichiaphages (0.018%), Enterobacteriaphages (0.018%), and Salmonellaphages (0.005%) were the most abundant bacteriophage families during exposure with antibiotics at day 7. At day 13 (3 days after the last day of antibiotic exposure), dominant members of the bacterial community structure seem to have recovered. However, differences on the taxonomic structure between day 0 and the post-antibiotic phase were significant   and 15.4 ± 0.2 , without a clear influence of the antibiotic treatment ). Relative abundance of 17 out of 23 functional cluster orthologous groups was significantly affected  during the antibiotic treatment compared to day 0. At the same time, genes coding for cytoskeleton  decreased by 2.5 times due to the antibiotic treatment. However, most pronounced changes were in the abundance of genes triggering the bacterial stress response. We found that two orthologous groups for SOS response recA/lexA (COG1974) and recA modulation activity (COG2137) significantly increased 5 and 13 times during the antibiotic exposure phase (P < 0.05 likelihood ratio test (LRT)) respectively. Genes coding for SOS response rise from 0.018 ± 0.001% at day 0 to 0.091 ± 0.009% at day 7 and recA modulation from 0.0008 ± 0.00003% to 0.0118 ± 0.001%. At day 13, 3 days after the antibiotic exposure, main functional patterns of the gut microbiome seem to recover and were comparable to the pre-exposure phase. However, differences in the total functional structure between day 0 and the post-antibiotic phase were significant  , reaching the maximum value 0.64 ± 0.08% at day 7, compared with 0.18 ± 0.02% at day 0 . Already at day 0, several ARGs were detected with mexQ as the most abundant, followed by macB, mexK, acrF, rpoB (S. aureus) mutation, and triC  and post-exposure (day 11), the floR gene was detected, which codes for resistance against florfenicol. This could indicate an enrichment due to the antibiotic pressure. All the floR genes were detected in plasmid sequences, 5 of them belonging to Proteobacteria. After the last day of antibiotic exposition, between days 11 and 13, the relative abundance and number of ARGs was comparable to day 0 and the control sample. However, total structure of ARGs was significantly different between the day 0 and days of the post-antibiotic phase being the day 34 the most variable  . Peptide drug class was the only one enriched significantly comparing day 0 and the post-antibiotic days 13, 18, and 26  . After the antibiotic exposure, the abundance of antibiotic efflux genes decreased at day 11 (0.106%) but slightly increased at day 13 (0.173%) after 3 days and 8 days  of post-exposure phase.Moreover, genes conferring resistance to eight and nine different drug classes were detected on day 0 and in the control samples, respectively Fig. b. This nP = 0.012) through the different phases was significantly different. The oral application of florfenicol increased the total MGEs in the gut of the animals . This indicates that the input of antibiotics contributes to the enrichment of MGEs in the gut of the animals. The most abundant MGE group identified at day 7 was transposases 0.613%, followed by phage integrases 0.401%, resolvases 0.088%, transposons (Tn3) 0.057%, other 0.025%, and RteC 0% . After day 26, 16 days after the antibiotic exposition, the total abundance of MGEs was comparable to day 0 and control sample.Relative abundance of MGEs . Therefore, a positive correlation between ARGs and MGEs co-occurring with ARGs was found , followed by gyrA (E. coli mutation), mexQ, mexK, and tetQ  , gyrB (S. aureus mutation), tetA, mdtM, acrF, and macB . Throughout the post-treatment, comparable to day 0 and the control sample, rpoB (S. aureus mutation) were the most abundant genes co-occurring with ARGs  followed by gyrA (E. coli mutation), acrF, and tetQ . Of all the ARGs, just TEM-190 (0.27%), QnrS1 (0.20%), tetG (0.13%), and floR (0.06%) were found close to a transposon (Tn3) in samples obtained during the antibiotic exposure phase and the first day of post-exposure (day 11). Before the antibiotic exposure, 1.26 and 0.84% of all ARGs were flanked by the MGEs phage integrases and IS21 respectively. During the antibiotic exposure phase, 1.72, 1.51, 1.03, 0.69, 0.69, and 0.69% of all ARGs were flanked by the elements phage integrase, IS21, transposase, transposon (Tn3), IS91, and IS3. During the post-treatment, IS21 (1.27%) was also found flanking several genes.We found a tendency for an increased frequency of co-occurrence between MGEs and ARGs comparing day 0 to 7  despite its relatively low abundance, followed by Citrobacter (20.1%), Klebsiella (9.05%), Plesiomonas (8.29%), Parabacteroides (3.22%), and Cetobacterium (2.46%). Further, 9.12% members of Enterobacteriaceae could not be assigned to a specific genus . Similarly, the most abundant genes for Plesiomonas were mexW, mexQ, and rpoB . After the antibiotic exposure treatment, Plesiomonas  and Cetobacterium (1.19%) remained as one of the genera harboring the most abundant ARGs. Interestingly, Bacteroides was the only taxa associated with ARGs found before the antibiotic and constant during the exposure phase. In addition, most of the ARGs identified before, during and after antibiotic exposure phase was associated with this genus (25–57%), mostly the gene mexQ (9.05–22.91%).The most abundant genes associated with tet) and sulfonamide (sul1) genes positively correlated to transposases in sediments from Baltic Sea fish farms and Chinese swine farms, respectively [IS21 and IS6 were the most abundant insertion sequences flanking ARGs during the antibiotic exposure. Interestingly, some members of IS6 interact with transposons, and IS21 has been reported to be associated with an increase of β-lactam resistance and to be involved in the mobility of ARGs coffering resistance to phenicols [IS21 was the most abundant insertion sequence found flanking ARGs before and after antibiotic treatment. This could indicate an important role of this element in the studied bacterial communities, possibly related to florfenicol pre-exposition.The effect of prophylactic, metaphylactic, and therapeutic administration of antibiotics on the gut bacterial communities of fish has received little attention so far. Instead, most of the studies have focused on the water columns and sediment of the farms applying aquaculture. We presume that the gut of the fish under antibiotic pressure is a perfect environment for the exchange of ARGs and MGEs. As predicted, we found that the abundance of ARGs and MGEs increased under antibiotic treatment. Furthermore, we observed a positive correlation between total ARGs and MGEs co-occurring with ARGs, showing a significant increase in potential mobilization of ARGs. This indicates that MGEs could be responsible for the prevalence of ARGs during the antibiotic pressure or a possible enrichment of taxa harboring ARGs co-occurring with MGEs. Similarly, it has been reported that tetracycline  efflux pumps and their expression was enriched at least 10 times during the antibiotic treatment [rpoB in Escherichia coli [rpoB and other genes were found flanked by phage integrases in our samples. Our results indicating an increase in the abundance of phages, phage integrases, and ARGs flanked by phage integrases strengthen the idea of phage as vehicles of antibiotic resistance in the presence of antibiotics.Phage integrases seem to play an important role in the exchange of genetic material under antibiotic pressure. Their increase came along with the detection of several phages during the antibiotic treatment, mostly Enterophages. Recently, it was reported that viromes from non-human sources including freshwater and marine environments are reservoirs of ARGs . Additioreatment . Also, ihia coli . Moreovehia coli . This ishia coli , which cblaTEM1a [TEM-190, QnrS1, tetG, and floR close to Tn3 can indicate that the use of florfenicol can promote the dispersion of transposons in aquaculture.In addition, Tn3 transposon was detected exclusively during the antibiotic input flanking tetracycline, β-lactamase, fluoroquinolone, and florfenicol resistance genes in low abundance. Tn3 transposons commonly carry antimicrobial passenger genes, recruit mobile integrons, and promote the exchanges of gene cassettes , 29. TheblaTEM1a . This coEnterobacteriaceae increased during the antibiotic exposure. The variability of plasmids able to facilitate antibiotic resistance in this bacterial family is high [E. aerogenes, E. cloacae, E. coli, K. pneumoniae, S. enterica, S. marcescens, S. sonnei, C. freundii, C. koseri, K. oxytoca, P. mirabilis, P. stuartii, and S. marcescens [Citrobacter, Klebsiella, and Salmonella were enriched during the antibiotic exposure in our study; this could be related to the presence of plasmids. For instance, all florfenicol resistance genes from our samples were identified as part of a plasmid, two of them associated with transposases, and one with Tn3. This finding indicates that florfenicol resistance and mobility in this environment could be mediated by plasmids. The origin of resistance to florfenicol has been under debate; it was initially detected in terrestrial bacteria associated with humans, but later it was found in a bacterium from aquaculture, which also indicates its mobility [floR in plasmid sequences, its emergence during antibiotic pressure, and its detection in terrestrial and marine environments represent a risk for the dissemination of antibiotic resistance.The rise of ARGs associated with plasmids carrying ARGs in our samples during the antibiotic exposure is a clear indication of potential mobility. Self-transmissible plasmids can promote horizontal gene transfer in an in vivo Zebrafish model without antibiotic pressure . This su is high . For exarcescens , 34. Citmobility , 36. Nowmobility , 38. ThefloR, pp-flo, fexA, flo, cfrC, and poxtA [floR was detected in our fish gut samples during antibiotic input. However, we could not see a specific increase in genes coding for phenicol resistance class, which is associated with florfenicol. This could be associated with fish larvae rearing with florfenicol administration. Additionally, tetracycline resistance genes were enriched, for example, tetA and tetG were found flanked by MGEs during the antibiotic exposure. It seems that tetracycline resistance genes are one of the most common drug classes found in fish feces [Aquaculture could be one of the main promoters of ARG enrichment in the environment . Our stund poxtA . Out of sh feces , fishmeash feces , and fissh feces . HowevermexQ, macB, and other several efflux pump genes were the most abundant ARGs in the gut of the fish, also without the pressure of antibiotic. These genes are related to multidrug and macrolides resistance. A previous study reported that independent from the exposure with sulfonamide-trimethoprim, feces from fish harbored multidrug/efflux and macrolide/efflux resistance genes as well as tetracycline and chloramphenicol resistance genes [In general, ce genes . Additioce genes . This coce genes , who desEnterobacteriaceae such as Citrobacter, Klebsiella, and Plesiomonas associated with ARGs. Members of these genera have been associated with nosocomial infections. For example, Citrobacter resistant to multiple β-lactamases [Klebsiella to β-lactamases, quinolones, and aminoglycosides [. Additionally, strains from these species are known for harboring plasmids with different resistance mechanism [. In addition, Citrobacter was isolated from diseased fish and farm-rise catfish, carrying ARGs as sulI, tetA, tetB, and other tetracycline genes [Citrobacter and Klebsiella were associated with plasmid-mediated quinolone resistance and Plesiomonas to β-lactamases. Therefore, florfenicol not only enriches potentially pathogenic bacteria but also promotes resistance to different antibiotics. Equally important, the findings in this study indicate that bacterial community harboring ARGs from the gut of farmed P. mesopotamicus is mainly composed by the genus Bacteroides. However, members of the phylum Proteobacteria carrying ARGs were more abundant during the input of the antibiotic. The abundance of Bacteroides carrying ARGs during the different phases of the experiment can be explained by the dominance of the phylum Bacteroidetes in the gut of the animal. Also, Bacteroides are naturally resistant to aminoglycosides, and some strains carry genes that provide resistance to penicillin, cephalosporine, tetracycline, and macrolides [Bacteroides fragilis increased in response to oxidative and bile/bile salts stress [Bacteroidetes was identified as a potential host of tetracycline resistance genes in an effluent of coastal aquaculture in South Korea [Bacteroides were associated with multiple resistance antibiotic efflux and target modification genes (rpoB and gyrB). It has been proven that mutation in gyrA and gyrB of B. fragilis confer resistance to fluoroquinolone [Bacteroides could be an important reservoir of antibiotic resistance because of its dominant abundance in the intestines of P. mesopotamicus. The detection of common bacteria from water and sediments and the emergence of pathogens during the exposition of antibiotic in fish increased the risk for public health and ARGs dispersion. Finally, our data and analyses provide a base for continuing the exploration of the mobilization of ARGs in the environment. Additionally, emerging technologies as long read-sequencing could be used as a next step to evaluate the synteny of different genes obtained from fish gut samples before during and after the antibiotic exposition. This could elucidate the potential transfer of genes in aquaculture.Bacteria from aquatic and terrestrial environments share several MGEs and ARGs , indicatctamases , 45 and ycosides  have beeechanism . In addine genes , 49. Thicrolides . In addis stress . Moreoveth Korea . In the uinolone . In thisEnterobacteriaceae members in the gut of the animal. We see an increased potential for the mobilization of ARGs during the antibiotic exposure. Additionally, the increased number of both plasmids and phages could facilitate the horizontal transfer of the mobilized ARGs. The fact that important nosocomial pathogens carrying several ARGs are enriched is alarming. Furthermore, the association of the most dominant taxa with multiple antibiotic efflux pumps and target alteration genes could be a signal of antibiotic resistance dissemination due to aquaculture practices. However, we cannot differentiate between the increased potential for ARG mobilization caused by the observed shift in the bacterial community and/or actual horizontal gene transfer and acquisition of ARG-MGE elements. Finally, most of the studies related to ARGs in aquaculture had focused on sediments and water samples, and few of them on the real-time transfers of the genes under antibiotic pressure. In this way, our study highlights the risk of using in-feed antibiotic during aquaculture production due to the potential increase of ARG mobilization and dispersion.Overall, our findings suggest that while the prophylactic use of antibiotics in fish aquaculture intends to contribute to its management, it might actually introduce several risks. The antibiotic pressure increases the bacterial stress response, the number of ARGs and MGEs, the co-occurrence of these elements, and enrichment of P. mesopotamicus were approved by the Ethics Committee for Animal Experimentation of the University of Campinas, Brazil (protocol #2015-39). One hundred fifty male juvenile animals, with an average weight of approximately 724 g , twice per day at 9 a.m. and 5 p.m. After the adaptation phase, the animals were randomly distributed between 10 tanks, which were operated under the same conditions as described above, resulting in 15 animals per tank. Animals in eight of the 10 tanks were fed for the period of 10 consecutive days with medicated feed, resulting in a dose of 9.7 mg florfenicol per kg and day. The FDA approved the use of a dose of 10–15 mg/kg body weight/day for 10 consecutive days of Aquaflor, which is mainly based on florfenicol, in recirculating aquaculture system [Piaractus mesopotamicus. The exposure phase was defined as the period when fish received the antimicrobial (day 1 to day 10). On day 11, the fish received only non-medicated feed and this phase is considered the depletion phase. Residues of florfenicol and florfenicol amine in the skin and muscle of the fish were 941, 388, 201, and 137 ng g−1 at days 11, 13, and 16 (not included in this study) respectively. After day 16, the antibiotic concentration was under detection limit. One tank was randomly chosen for each sampling time point, and three fish were collected and treated as true replicates for the metagenomics analysis. Animals were sacrificed using a solution containing 500 mg L−1 benzocaine. The gut samples were collected at least 4 h after the fish feeding in the morning period. The abdominal cavity was dissected and the gastrointestinal tract was aseptically and immediately collected. Fecal material was removed by gentle squeezing the distal section of the intestine (S3 to rectum) [All experiments and protocols using e system . The rem rectum) , 56. Sam rectum) .Metagenomic DNA was extracted using the QIAmp fast DNA Stool Mini Kit  following the manufacturer’s instructions. Only two DNA extractions from sample day 11 yielded enough DNA for the preparation of metagenomics libraries, and obtained results from the corresponding samples were highly variable. DNA concentrations were measured using Quant-It™ PicoGreen® dsDNA Assay Kit  and a spectrofluorometer . DNA purity check was assessed spectrophotometrically . In total ~ 100 ng of DNA per sample was sheared using an E220 Focused-ultrasonicator  targeting 500 bp fragments following Covaris’s instructions. Metagenomic libraries were constructed using NEBNext® Ultra™ DNA Library Prep Kit for Illumina®. Dual indexing was done using the kit NEBNext® Multiplex Oligos for Illumina® . Purification and size selection was performed based on Agencourt® AMPure® XP . Libraries inserts ranged between 500 and 700 bp were evaluated using a Fragment Analyzer™ . One sample with sterile water was used as a control for the metagenomics library preparation and sequencing. Libraries quantification were performed using Quant-It™ PicoGreen® dsDNA Assay Kit and sequenced on an Illumina MiSeq  using the paired-end mode (2 × 300 bp).Pygocentrus nattereri (BioProject: PRJNA331139) and Astyanax mexicanus (BioProject: PRJNA237016) for a Deconseq-decontamination step due to the absence of P. mesopotamicus genome. Clean reads were taxonomically classified by Kaiju v1.4.5 [Adapters and primers were removed from raw reads using Adapterremoval v.2.1 . Nucleotu v1.4.5  in a greu v1.4.5  was usedu v1.4.5  and Diamu v1.4.5  using thu v1.4.5 , and besTotal cleaned reads were assembled using metaSPADES v 3.10  with a mARGs were detected with Resistance Gene Identifier v3.1.1 and “The Comprehensive Antibiotic Resistance Database” (CARD)  using “s−5 e-value were retained, and the best hit per read was used for further analysis. MGEs were grouped into six groups based on identified MGEs: phage integrases, transposons (transposases related to a specific transposon), transposases, RteC (related to tetracycline transposon), resolvases, and others. Position and co-occurrence of ARGs and MGEs were analyzed using in-home scripts. Additionally, co-occurrence of genes was curated manually. Co-occurrence was considered positive if an antibiotic resistance gene was found within ten open reading frames from upstream or downstream a mobile genetic element gene. Details about this can be found in  were used for preparing a ternary plot. The dissimilarity between the taxonomical, functional, and ARG bacterial structure of the day 0 and post-antibiotic phase was explored using the Bray-Curtis dissimilarity measure and represented using a Non-metric Multidimensional Scaling (NMDS) plot. Additionally, dissimilarity was tested using Adonis test (permutation = 999). Multivariate homogeneity of group dispersions was also tested. Samples from the antibiotic phases and day 11 (post-antibiotic) were excluded to observe the differences. Vegan v.2.4-2 package was used for this analysis. Differences in the relative abundance of ARGs, MGE, and fold change between drug classes were evaluated using robust one-way ANOVA and robust post hoc Rand Wilcox’s based on trimmed means and percentile bootstrap [t1way  and mcppb20 (bootstrap = 2000 and trimmed mean = 20%) functions implemented by Wilcox were utilized for the analysis. Differences in the relative abundance of ARGs and MGEs between days 0 and 7 were explored using the Jonckheere–Terpstra test implemented in the clinfun R-package [bootTau (bootstrap = 2000). All the Wilcox’s functions can be found in [Statistical analysis and plots were created using R v3.3.1., SigmaPlot v12., and LefSe-Galaxy v1.0. Linear discriminant analysis (LDA) was used to determine biomarkers for every treatment using LEfSe . Only foootstrap . Here, t-package . This tefound in . Total rAdditional file 1:Figure S1. Variation of weight of the sampled fish before, during and after exposure to florfenicol. Figure S2. Coverage/number of raw reads (A) and Nonpareil index diversity (B) from the bacterial community of Piaractus mesopotamicus before during and after antibiotic exposure. The index indicates the complexity of the bacterial community in terms of “Sequencing space”. Higher values indicate higher diversity. Figure S3. Effect of florfenicol on the relative abundance of the families (A) and genus (B) of the bacterial community of Piaractus mesopotamicus before, during, and after antibiotic exposure.Figure S4. Taxonomic (A), functional (B), and ARGs (C) structure of the gut bacterial community of Piaractus mesopotamicu before (day 0) and after antibiotic exposure . Figure S5. Effect of the antibiotic florfenicol on the relative abundance of ARGs (A) and MGEs (B) of the gut bacterial community of Piaractus mesopotamicus before, during and after antibiotic treatment. Figure S6. Fold changes of different drug classes after the antibiotic treatment. Figure S7. Antibiotic resistance genes from plasmid origins. Figure S8. Correlation of total ribosomal protein L1 (A) and L12 (B) and the same genes co-occurring with MGEs genes before, during and after antibiotic exposure. Figure S9. The 30 Most abundant ARGs flanked by MGEs in the gut of Piaractus mesopotamicus before, during, and after antibiotic exposure. Figure S10. The eight most abundant genus (contigs) harboring ARGs from gut samples of Piaractus mesopotamicus before, during and after the antibiotic exposure. Table S1. Bacterial functional shift in the gut of P. mesopotamicus before, during, and after antibiotic exposure. (DOC 5958 kb)Additional file 2:The file is the script used to find the genes co-occurring with the ARGs detected. (RB 4 kb)


Given the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor. Infectious diseases have been a challenge throughout the ages. From 1347 to 1350, approximately one-third of Europe’s population perished to Bubonic plague. Advances in sanitary and hygienic conditions sufficed to control further plague outbreaks. However, these persisted as a recurrent public health issue. Likewise, infectious diseases in general remained the leading cause of death up to the early 1900s, e.g., accounting for 25% of England’s mortality. However, by the mid-1900s, the mortality of infectious diseases in England shrunk to under 1% after the commercialization of antibiotics [The term ‘antibiotic’ was introduced by Selman Waksman as any small molecule, produced by a microbe, with antagonistic properties on the growth of other microbes . An antiCurrently, more than 2 million North Americans acquire infections associated with antibiotic resistance every year, resulting in 23,000 deaths . In EuroThe increase in drug-resistant pathogens is a consequence of multiple factors, including but not limited to high rates of antimicrobial prescriptions, antibiotic mismanagement in the form of self-medication or interruption of therapy, and large-scale antibiotic use as growth promotors in livestock farming . For exaThe systematic procedures—Antibiotic Discovery Platforms (ADPs)—behind the discovery of major antibiotic classes, which fueled the antibiotic golden age, have become exhausted. Modern ADPs have yielded redundant discoveries and/or failed in translation to the clinic, which dimmed the overly optimistic expectations created with the development of novel technologies throughout the genomics era. From 2004–2009, the overall rate of antibacterial approval was a mindboggling single drug per year , which dDuring 2011, the director general of the World Health Organization made the clear forewarning that we are currently “on the brink of losing these miracle cures… In the absence of urgent corrective and protective actions, the world is heading towards a post-antibiotic era, in which many common infections will no longer have a cure and, once again, kill unabated” . BesidesPseudomonas aeruginosa extracts. While their investigation was discontinued due to inconsistent effects, the antimicrobial effect observed was later associated with quorum-sensing molecules [Traditional behaviors and primitive rituals suggest ancient human use of antibiotics ,29, altholecules . When diolecules ,32,33,34olecules . Ehrlicholecules , the firolecules .The systematic application of chemical modifications to expand a library of lead molecules, followed by screening its effect on a disease model contributed to the discovery of Neosalvarsan, a more water-soluble derivative with reduced side effects, and laid the foundation of modern pharmaceutical research. Given its success, the Friedrich Bayer Company explored synthetic chemicals for therapeutic purposes in the 1920s . The azoArguably, it was Alexander’s Fleming ‘accidental’ detection of Staphylococci growth inhibition around mold colonies in petri dishes, forgotten at his lab throughout a holiday period, that mostly impacted the future of antimicrobial discovery . FlemingAlthough penicillin’s bioprocess scale-up breakthroughs enabled its widespread clinical use during the late period of World War II, efforts pursued an outperforming chemical synthesis protocol. During late 1945, penicillin antimicrobial activity was traced to the B-lactam ring . Ernst CImpelled by the remarkable successes at the beginning of the 20th century, Selman Waksman adventured into the realm of drug discovery. In 1937, noticing that complex soil bacteria—actinomycetes—inhibited the growth of other bacteria, Waksman acknowledged that these biological mechanisms, which evolved from competitive growth , could bStreptomyces griseus strain was found to produce a non-toxic aminoglycoside antibiotic, named streptomycin, which inhibits protein synthesis by binding to the bacterial 30S ribosomal subunit. At the time, it was not possible to patent natural products in the USA, but together with Merck lawyers, Waksman convinced the authorities that purified antibiotics were sufficiently distinct, sparking a new range of business opportunities, a significant stride towards economic stimulus that bolstered the antibiotic golden age. Merck obtained FDA approval for streptomycin [The Waksman platform promptly revealed new antimicrobials: actinomycin, streptothricin, fumigacin and clavacin; but it was not until 1944 that a ptomycin . The WakStreptomyces venezuelae, thereby introducing the amphenicol class. Chloramphenicol’s antimicrobial activity derives from its reversible binding to the 50S ribosomal subunit, thereby inhibiting bacterial protein synthesis. It was the first FDA-approved broad-spectrum antibiotic, displaying excellent tissue and fluid permeability. However, in the 1960s, various toxicity issues impaired its administration, and it is currently rarely prescribed [Streptomyces aureofaciens, is characterized by its instability at both ends of the pH scale that hampers its bioavailability [Chloramphenicol was originally isolated in 1947 from the actinomycete escribed . Chlorotlability . Saccharopolyspora erythrea. Erythromycin binds to a 50S bacterial ribosomal target, but its therapeutic use was characterized by instability under acidic conditions and overall poor oral bioavailability [Streptomyces virginiae in 1952. Streptogramins are a class of antibiotics formed by two chemically unrelated substances, a polyunsaturated macrolactone and a cyclic hexadepsipeptide. Either group binds to the 50S subunit of bacterial ribosomes, presenting mediocre activity, but their synergistic effect empowers its therapeutic application [Macrolides are the second most prescribed class of therapeutic antibiotics, introduced in 1949 with erythromycin and produced by lication .Amycolatopsis orientalis and is currently a last resort antibiotic. Vancomycin interferes with the transpeptidation and transglycosylation steps of the cell wall synthesis, thereby inhibiting cross-linking and cell wall maturation [Streptomyces mediterranei (later classified as Amycolatopsis mediterranei), and despite considerably low antimicrobial effect, it introduced a unique metabolic target in bacteria [Streptomyces strains in 1969. Its antimicrobial effect derives from the inhibition of the initial steps of the cell wall biosynthesis pathway, disrupting the action of phosphoenolpyruvate synthetase. However, fosfomycin presents a broad spectrum of activity, making it an appealing antimicrobial [Unlike the antibiotic classes described thus far, which target bacterial protein synthesis, glycopeptides disrupt cell wall synthesis. The first antibiotic of the glycopeptide class, vancomycin, was discovered in 1956 to be produced by turation . Similarbacteria . The disicrobial . Paenibacillus polymyxa, the therapeutic use of this class was limited to experimentations for a mere couple of years, given multiple concerning adverse effects, but has recently been reconsidered [Streptomyces roseosporus was revealed in 1980 and although Eli Lilly and Co. attempted its commercialization, clinical trials were discontinued under the belief that there was a small window between therapeutic efficacy and safety. As such, this calcium-dependent cyclic lipopeptide is seen as the precursor of the lipopeptide class of antibiotics, with surpassing antimicrobial activity in comparison with polymyxin E, albeit limited to Gram-positive pathogens. Interestingly, daptomycin was revived by Cubist Pharmaceuticals and, with dosing adjustments, reached the market by 2003 [Although the first report of a lipopeptide antibiotic dates to 1947 with the discovery of polymyxin E, produced by nsidered . The pro by 2003 . Moreove by 2003 .Antibacterial semi-synthesis is the modification of existing scaffolds, or molecular backbones, obtained by a fermentative procedure. Historically, most scaffolds originated from the Waksman platform. Thus, they are the evolutionary outcome of selective pressures, e.g., from the actinomycete-bacteria ‘fight’, and are therefore extremely well fit to reach and bind to their target. However, this does not translate to therapeutic effectiveness or safety, which can often be improved by means of semi-synthesis, alongside its chemical stability, reduction of undesirable side effects, among other features that are crucial in marketing antibiotics, for instance patenting derivatives, which increases profitability of antibiotic development programs, essential for this generally unattractive business. Semi-synthesis began with the catalytic hydrogenation of streptomycin, which resulted in dihydrostreptomycin by 1946, and was characterized by greater chemical stability along with similar antimicrobial activity. Although both streptomycin and its novel derivative quickly made their way to clinical use, eventually their prescription has been reevaluated due to ototoxicity concerns . Conversely, it took over a decade before a bioproduction method made penicillin a therapeutic possibility. While the identification of penicillin’s antimicrobial effect preceded its ‘discovery’, it was Fleming’s will power that pushed penicillin beyond only being obtainable in small and unstable quantities. This in turn enabled its semi-synthesis, which expanded penicillin from a single drug to a range of semi-synthetic derivatives constituting an entire class of antibacterial drugs, the beta-lactams. These comprise over 60% of antibiotics for human use , with a Cephalosporium acremonium in 1948. By 1959, 7-aminocephalosporanic acid (7-ACA) was obtained from its hydrolysis under acidic conditions, thereby introducing the precursor to a multitude of semi-synthetic cephalosporins [Semi-synthetic penicillins are obtained by producing penicillin G, which is hydrolyzed into 6-APA, purified and later chemically altered, e.g., at the acyl side chain, to achieve various semi-synthetic penicillins . Anotherosporins . Figure Another key illustration of semi-synthesis comes from the catalytic hydrogenolysis of chlorotetracycline (discovered in 1948), which resulted in the semi-synthesis of tetracycline by 1953, although it was later also found to be a natural product . While sFully synthetic antibiotics, beyond introducing novel molecules, enable production at a scale suitable for clinical application. For instance, chloramphenicol became the first fully synthetic antibiotic, whose scaffold originated from a natural product, to reach the clinic in 1949. Unsurprisingly, the rational of semi-synthesis, that of chemically manipulating a scaffold, applies to a fully synthetic antibiotic like chloramphenicol. In fact, replacing the nitro group with methanesulfonyl resulted in thiamphenicol in 1952, which overcame the most concerning toxicity issues and had greater antimicrobial effect, thereby improving its clinical application . The disMost of the fully synthetic antibiotics discussed have limited application to uncomplicated infections or as an economic alternative in developing countries. The quinolone class, which was unexpectedly discovered as a by-product of the synthesis of the antimalarial compound chloroquine, despite limited activity, was an important scaffold in the synthesis of nalidixic acid in 1962 . Three mThe case of fully synthetic beta-lactams is of paramount relevance since it allowed to more intricate antibiotics to be synthetized, eventually leading to a panoply of subclasses. Two important examples are the subclasses of carbapenems and monobactams. Carbapenems have a similar core structure to penicillins, differing at the C2–C3 double bond and the replacement of C1 sulfur for carbon, yielding improved potency, spectrum of activity, and better resistance to the action of beta-lactamases. Currently, 10 carbapenems derivatives have been marketed, or are under clinical development, since their discovery in 1985. Given that carbapenems have the widest activity spectrum among beta-lactams, including resistant pathogens, they are currently a first in line option for treating multidrug-resistant infections . LikewisThe class of oxazolidinones is divided into two groups differing in their mode of action. The first acts on cell wall biosynthesis and was introduced with the natural product cycloserine in 1952, which is currently produced by synthetic means. Cycloserine is still used as a second-line therapeutic option for tuberculosis, especially in its multidrug-resistant form. The other group of oxazolidinones was found in 1984 to target protein synthesis and, despite reasonable antimicrobial activity, presented limiting toxicity issues . From thAfter the successes of the antibiotic golden age, the discovery rate of the underlying ADPs has decreased, along with an increase in class and multidrug-resistance mechanisms, which has weakened the therapeutic efficacy of the antibiotic arsenal and revived the issue of infectious diseases. The need for a new strategy coincided with the genomics era, which redefined the scientific paradigm governing antibiotic discovery and shaped new high-tech platforms. During the genomics era (1995–2004), the total number of sequenced microbial genomes increased from 3 to over 200 , and in Given that a manageable number of proteins are exclusive and conserved in bacteria, new MOAs were expected to surface, so some companies launched pioneering target-based screening programs. GlaxoSmithKline developed a target list of over 300 bacterial genes from 1995 to 2001, of which approximately 160 were considered essential for survival, and deemed ‘druggable’ in the search for broad-spectrum antibiotics . Elitra Despite the massive bacterial genome sequencing coupled with the development of bioinformatics tools to analyze said sequences, there are still many genes whose biological function has not been characterized. Moreover, genetic diversity further complicates target-based screening at the level of model organism selection, e.g., GlaxoSmithKline researchers reported an unrelated copy of genes conferring resistance in 20% of clinical isolates . UltimatThe case of anti-tuberculosis drug discovery is a good example of this change in strategy: researchers moved away from target-based ADPs and returned to cell-based screening , with grBacillus subtilis strains, modified with luciferase reporter genes, to indicate the MOA of various antibiotics with sensitivity ranging from generic pathways, antibiotic class and the specific MOA of some drugs.In a broad sense, cell-based assays include screening large libraries in a systems-based mentality in order to evaluate the complex network of responses that antibiotics elicit , and areAlternatives to MIC-type assays require genetic manipulation and/or the use of a label, either in the form of a fluorescent or radioactive molecule, or a reporter gene. This is a limiting factor since, on the one hand, genetic manipulation implies a priori knowledge and on the other hand, the indication of gene transcription using a reporter gene may not always be coherent with alterations of enzymatic activity, thereby crippling the inherent sensitivity of these assays. Moreover, these signal transduction events can take considerable time to become detectable, thus limiting assay capacity and throughput . In addiMycobacterium tuberculosis. From these five new drugs, three are derived from natural products , and only two were chemically synthesized (linezolid and bedaquiline) [Eder et al. reviewed the discovery platforms of first-in-class small molecule drugs, in particular the role of target- versus cell-based screening . First-iquiline) . Historically, the success of antibiotic therapy relied on the discovery of natural scaffolds that were chemically optimized or produced. As such, it remains a rational decision to continuously develop screening strategies that probe natures repositories , especiaBiological research tends towards specialization, through increasingly focused and localized research; however, system-wide understanding of the biological constituents and their interactions is gaining importance. It is now possible to extract, handle and interpret information from much higher dimension and diverse origins, such as transcripts , proteins (proteomics), and other molecules such as lipids (lipidomics), etc. The influence of these omics technologies on the field of antibiotic discovery is undisputable, especially in understanding antibiotics MOA, identifying novel targets, and supplying insights to bacterial metabolism and physiology. Given the importance of screening in the ADPs discussed thus far, this mindset should be the backbone of future platforms. However, neither transcriptomics, proteomics nor lipidomics have matured to the throughput capacity of cell-based screening assays, and therefore are not the core technology of any ADP. These technologies convey insight on the biomolecules they probe, and not the holistic dynamics of bacterial metabolism, thereby serving as complementary, albeit crucial, tools for the antibiotic discovery process. Since a post-genomics ADP is yet to be developed, this section focusses on the technological basis and contribution of these post-genomics techniques to the field of antibiotic discovery.Initial transcriptomics technologies were hybridization-based, e.g., Northern Blotting and microarrays . MicroarGenome expression technologies expand beyond the transcript level to biological events at the level of proteins. Not only do these occur without transcriptome alterations, but the instability of bacterial RNA raises both conceptual and technological limitations, which stress the need to complement transcriptomics with proteomics. Early proteomics studies relied on 2D gel-based assays or on Difference Gel Electrophoresis , which rUnderstanding the physiological role of lipids, especially at the molecular level, has been considerably limited due to a technological gap that is being filling with very selective and sensitive lipidome characterization studies using MS, and combining various targeted and non-targeted approaches . To achiEscherichia coli. Moreover, metabolomics complements other omics, for instance, rhodomyrtone’s antimicrobial activity was identified via phenotypic screening, but its MOA was revealed with proteomics and metabolomics. Specifically, rhodomyrtone cripples capsule biosynthesis enzymes and metabolites of Streptococcus pneumoniae [Gene expression data from transcriptomics and proteomics faces challenges, for instance, increases in RNA levels might not coherently result in changes at the protein level, added to conceptual and technological limitations associated with bacterial RNA instability, and differences in protein levels are often poor estimators of metabolic activity. Consequently, interest in small-molecule metabolites has also emerged . Metaboleumoniae . Additioeumoniae . Metagenomics, and meta-omics in general, have reinforced natural product discovery, which has had a central role in antibiotic discovery, and chemotherapy in general, ranging from oncological to immunologic treatments, e.g., approximately 50% of all FDA-approved therapeutics are natural products or their derivatives . MetagenAquabacteria, was shown to produce an antibiotic named teixobactin, a peptidoglycan synthesis inhibitor. Teixobactin is mostly active against Gram-positive pathogens, some of which are drug-resistant, and its bactericidal activity even surpasses that of vancomycin (a last resort antibiotic), along with no indication of resistance mechanisms currently existing [An interesting device, the iChip, allows for the high-throughput cultivation of microbial species in their natural habitat, with a growth recovery of 50% versus 1% of traditional recovery methods, thereby giving access to otherwise ‘uncultivable’ microorganisms . The iChexisting . Metagenexisting . Staphylococcus lugdunensis nasal colonization, these commensal bacteria inhibit the presence of Staphylococcus aureus strains, thereby preventing opportunistic infections. This effect was traced to the production of lugdunin, a novel class antibiotic (macrocyclic thiazolidine peptides) produced by S. lugdunensis, which has bactericidal activity on key pathogens and importantly, presents a reduced risk of resistance development [Clostridium difficile infections have been treated with complete microbiome transplantation [The interaction of antibiotics with the human microbiome has also been enabled by meta-omics, which has created further opportunities for antibiotic discovery . In factelopment . Likewiselopment . On a diantation , which iAs seen, the technologies introduced in the post-genomics era have contributed towards new opportunities in antibiotic research, although these have not been at the core of any ADP. The case of teixobactin, for instance, heavily relied on the revelations brought by meta-genomics and the technologies required to build a device such as the iChip. However, identifying which of the molecules recovered with the iChip have antimicrobial activity, along with insights into their MOA, were revealed with cell-based assays in a reverse genomics platform. Since phenotypic screening has had greater success in revealing first-in-class molecules, it is a great starting point for ADPs. However, the drawback is the reduced mechanistic information derived, for which the omics technologies supply accelerated insight on the MOA, including the molecular target and its regulation. Then, with the required mechanistic information, target-based screening can be applied in order to optimize lead molecules into best-in-class medicines . AlthougOnce considered a resolved health issue, infectious diseases have resurfaced as a topic requiring urgent action. Antibiotic discovery has come a long way since the success of the Waksman platform, semi-synthesis and fully synthetic ADPs. As seen, the establishment of systematic procedures—platforms—was crucial for the discovery of the major antibiotic classes in use. Given the limitations of target-based screening, cell-based ADPs were revived during the genomics era. While some consider the genomics era platforms disappointing, the importance of the lessons learned should not be minimized. Considerable technological advances have given researchers unprecedented access to biological events and repositioned the mind-set for antibiotic research in a systems biology context. Paradoxically, in the field of antibiotic discovery, the more we know the less we can discover. Although not at the core of any ADPs, omics technologies have been proven of unquestionable value as auxiliary tools for antibiotic discovery. Importantly, cell-based screening requires MOA characterization, for which omics technologies are indispensable. Despite offering added-value information on biological events, their reduced throughput capacity alongside complementarity, in terms of resourcing to multiple omics simultaneously, implies a limited application in ADPs aiming to screen large libraries, for instance the reservoir of untapped natural products, which is likely the next antibiotic ‘gold mine’. There is a void between phenotanypic screening (high-throughput) and omics-centered assays (high-information), where some mechanistic and molecular information complements antimicrobial activity, without the laborious and extensive application of various omics assays. Given the novelty of the various omics technologies, we are yet to extract their full potential and it seems feasible that these technologies will mature to fulfill this gap. Alternatively, innovative technologies favoring high-throughput may be developed, even by sacrificing molecular sensitivity to some extent. In any case, the increasing need for antibiotics drives the relentless and continuous research on the foreground of antibiotic discovery. This is likely to expand our knowledge on the biological events underlying infectious diseases and, hopefully, result in better therapeutics that can swing the war on infectious diseases back in our favor.


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