Belonging to the betacoronavirus family, it primarily spreads through human contact via symptomatic and asymptomatic transmission. Despite several attempts since it emerged, there is no known treatment in the form of drugs or vaccines. Hence, work on developing a potential multi-subunit vaccine is the need of the hour. In this study, attempts have been made to find globally conserved epitopes from the entire set of SARS-CoV-2 proteins as there is as yet, no clear information on the immunogenicity of these proteins. Using diverse computational tools, a ranked list of probable immunogenic, promiscuous epitopes generated through all the three main stages of antigen processing and presentation pathways has been prioritized. Moreover, several useful insights were gleaned during these analyses. One of the most important insights is that all of the proteins in this pathogen present unique epitopes, so that the targeting of a few specific viral proteins is not likely to result in an effective immune response in humans. Due to the presence of these unique epitopes in all of the SARS-CoV-2 proteins, stronger immune responses generated by T cell hyperactivation may lead to cytokine storm and immunopathology and consequently, remote chances of human survival. These epitopes, after due validation  It causes COVID-19 disease with significant mortality rate. As there is currently no known cure, urgent studies are needed in order to push forward drug and vaccine design and development. Recently, about 77 drugs were identified by the world's fastest supercomputer, Summit, against viral spike protein [in silico approaches will be significantly useful in helping develop a preventive approach or a cure in as fast a manner as possible. Vaccines can be administered as prophylactic and even as therapeutic vaccines; as an example, anti-HBV vaccines are currently being developed as therapeutic vaccine candidates. Cytotoxic T cell immune responses have been observed in close relatives, SARS and MERS [Novel coronavirus SARS-CoV-2), also known as 2019-nCoV, first emerged in population in December 2019 and has rapidly gained foothold across the world resulting in WHO declaring it as a pandemic  is 29 882 bp in length. Being 100% identical to the reference sequence NC_045512.2 from Wuhan, China, it harbours multiple structural, non-structural and accessory proteins essential or playing a role at various stages of the viral life cycle. This SARS-CoV-2 genome is found 82.3% identical to SARS-CoV genome (NC_004718.3), using NCBI BLASTn tool. In brief, the sequence of proteins in its RNA genome as per this GenBank accession information  is as foet al. [While the structural proteins, S, E, M and N, are key proteins, several proteins such as ORF3a, ORF7a and ORF8 function as accessory proteins playing a role in the viral pathogenesis. ORF1ab, a polyprotein, encodes several non-structural proteins, 15 in number, identified in this genome sequence annotation, including RNA-dependent RNA polymerase (RdRP). The role of structural proteins is determined from their homology to SARS-CoV as well as a few experiments . The expet al.  have cloet al. , whereinThe advantages of epitope-based subunit vaccines as opposed to DNA and live attenuated virus vaccines is that these do not contain live components and so are considered safe. Moreover, these present an antigen or a set of antigens to the immune system with lower risk of side effects . These a2.2.1.in vitro and in vivo, too. Further, conserved residues between SARS-CoV-2 and other HCoV and MERS species were found from multiple sequence alignments (MSAs) and found in several of these epitopes . As the NCBI RefSeq sequence of SARS-CoV was unclear in the proper annotations for respective proteins, it could not be used in MSA studies. It is observed that most of the epitopes with conserved residues belonged to ORF1ab region . The alleles present in CD4episcore are: HLA-DRB1:03:01, HLA-DRB1:07:01, HLA-DRB1:15:01, HLA-DRB3:01:01, HLA-DRB3:02:02, HLA-DRB4:01:01 and HLA-DRB5:01:01.Helper T lymphocyte epitopes are typically 15 amino acid residues long. High throughput data for these epitopes was analysed manually to identify common epitopes across alleles and 10 coronaviral proteins.From NetMHCIIpan studies, a total of 1802 promiscuous HTL epitopes  selected till rank 2% which are strong binders  were generated. Among these epitopes, 649 epitopes (15-mer) were found to be immunogenic by CD4episcore across all alleles. Another immunogenicity prediction tool, ITcell, was used to predict immunogenic epitopes across only two alleles, DRB1*01:01 and DRB1*15:01, as it uses PDB files for TCR which are available for these two DRB1 alleles, and there was no TCR structure in PDB for other HLA class-II alleles studied. Also, ITcell predicts 12-mer HTL epitopes. Taking ITcell results into account, top-scoring common immunogenic epitopes to both these immunogenicity prediction tools were 95 in number and were taken for further analysis. These also included some of the epitopes binding to the other HLA-DRB1 alleles studied. This can be explained on the basis of observations that among all HLA-II molecules, there exists a high degree of repertoire overlap, reflecting multiple binding partners. This is most probably due to the backbone interactions rather than anchor residues playing a major role . Among t2.3.Bar diagram for CTL and HTL immunogenic epitope distribution across proteins  shows a Venn diagram depicted a common list of many epitopes from a single protein across alleles . A distinct pattern is to be noted; analysis of HTL epitopes belonging to HLA-DRB1*03:01, HLA-DRB1*11:01 and HLA-DRB1*15:01 indicated the lowest number of common epitopes or none at all across most of the proteins, and can be considered outlier epitopes. Envelope protein was unique in the sense that it did not provide either strong or weak binders to HLA-DRB1*03:01 allele, frequent across North America, Europe, India and Africa. ORF10 was also unique in providing only weak HTL binders to all of the alleles studied. Venn diagram of all these cytotoxic and helper T cell epitopes taken together showed no common epitopes at all across proteins, but within a given protein set, common epitopes could be found. This observation indicates that every protein of SARS-CoV-2 may present antigenic epitopes to the immune system, resulting in a high number of targets. This further lends credence to the theory that multiple T cell epitopes may elicit an immune response in each case, some eliciting strong and some providing weaker responses and therefore, there may be high degree of T cell immunopathology at the infection site. Stronger T cell immune response may cause even the normal, uninfected cells to be attacked while weaker helper T cell immune response, in some protein targets, may cause weak neutralizing antibody responses as well as weak CTL response at varying times during infection. Very recently, one study has pointed to this immune dysregulation  in COVIDet al. [et al. [et al. [et al. [While this study was at the writing stage, two studies on T cell epitope generation using all proteins ,27 were et al.  study in [et al.  focused  [et al. , and wer2.4.All of the 1924 CTL and HTL topmost epitopes (122 CTL epitopes and 1802 HTL epitopes) across the proteins studied, of which 1096 were non-redundant, unique epitopes, were then clustered using IEDB epitope cluster analysis tool  to make The larger clusters harbouring consensus sequences were: VDFQVTIAEILLIIMRTFKVSIWNLDYIINLIIKN (23 members), KLWAQCVQLHNDILLAKDTTEAFEKMVSLLSVLLSM and TQHQPYVVDDPCPIHFYSKWYIRVGARKSAPLIEL (20 members each). These clusters across proteins and alleles may be considered immunodominant epitopes and tested first among the ranked list of epitopes.Among immunogenic 122 CTL epitopes from IEDB and 666 HTL epitopes from CD4episcore, again HLVDFQVTIAEILLIIMRTFKVSIWNLDYIINLII topped the list. Further, among the same immunogenic 122 CTL and 95 HTL epitopes common to two prediction algorithms, CD4episcore and ITcell, VTIAEILLIIMRTFKVSIWNLDYIINL belonging to ORF6 again topped. Moreover, PIHFYSKWYIRVGARKSAPLIEL belonging to ORF8 and MGYINVFAFPFTIYSLL belonging to ORF10 were also among the top three clustered sequences. It is of interest to note that sequences in the consensus sequence MGYINVFAFPFTIYSLL belonging to ORF10 are weak binders to all the HLA-DRB1 alleles studied, while the nonameric sequences in this consensus sequence are strong binders to all HLA-I supertypes studied.2.5.Cross-reactivity analyses against human proteome based on UniProt data  indicate2.6.in vitro and in vivo experiments.The widespread presence of novel, unique T cell epitopes in the SARS-CoV-2 proteome, is also the main reason that in this paper, B cell epitopes were not studied. Further, including B cell epitopes in the vaccination strategy with T cell epitopes may not be a good strategy, and may even be counter-productive. Even though neutralizing antibody levels are found to be low in COVID-19 patients ,30, it iin vitro testing for further refinement and development as potent immunogens to be incorporated as components of multi-subunit vaccines.While many of the proteins studied are found to be expressed and also their functions known by virtue of homology with SARS-CoV, many of the novel ORFs including ORF8 and ORF10 need to be experimentally tested for their functional validation. Experimental MHC-peptide binding and T cell stimulation assays are now required for 3.in vitro and in vivo assays and saving their time and costs involved in our urgent bid to tackle SARS-CoV-2 infections and ensuing death. This essential list of highly probable epitopes opens up avenues for developing prophylactic and therapeutic interventions and for further understanding of the human immune system responses to this virus.Utilizing all 10 of the SARS-CoV-2 proteins, predicted or otherwise, a ranked list of CTL and HTL epitopes with high HLA-binding affinity, high TAP transport efficiency and high C-terminal proteasomal cleavage ranking has been generated. Incorporating the alleles predominant in the whole world population, two different prediction algorithms were implemented in the identification of common epitopes for creating consensus. Immunogenicity scores for these epitopes have also been predicted in order to further narrow down the list to a few key epitopes that can be experimentally tested. Peptide matching with the human proteome showed no indication of possible cross-reactivity. These epitopes are provided to the scientific community for further development using 4.4.1.The genome sequence of novel coronavirus was retrieved from GenBank accession number MT106054.1/RefSeq sequence number NC_045512.2 and the corresponding proteins were retrieved. RefSeq sequences of all of the proteins present in this genomic sequence, ORF10 protein (YP_009725255.1), nucleocapsid phosphoprotein (YP_009724397.2), ORF8 protein , ORF7a protein (YP_009724395.1), ORF6 protein (YP_009724394.1), membrane glycoprotein (YP_009724393.1), envelope protein (YP_009724392.1), ORF3a protein (YP_009724391.1), surface glycoprotein (YP_009724390.1) and ORF1ab (YP_009724389.1) were analysed in order to cover the entire genome of SARS-CoV-2 in view of absence of data on its virulent proteins. Within ORF1ab (full protein accession number: YP_009724389.1), the accession numbers of the following proteins taken were as follows: leader protein—YP_009725297.1, nsp2—YP_009725298.1, nsp3—YP_009725299.1, nsp4—YP_009725300.1, 3C-like proteinase—YP_009725301.1, nsp6—YP_009725302.1, nsp7—YP_009725303.1, nsp8—YP_009725304.1, nsp9—YP_009725305.1, nsp10—YP_009725306.1, RNA-dependent RNA polymerase—YP_009725307.1, helicase—YP_009725308.1, 3′-to-5′ exonuclease—YP_009725309.1, endoRNAse—YP_009725310.1 and 2′-O-ribose methyltransferase—YP_009725311.1. Fasta sequences of all of these proteins were taken as inputs in several T cell epitope prediction and analysis tools.4.2.http://www.cbs.dtu.dk/services/NetCTLpan/, [http://www.cbs.dtu.dk/services/PickPocket/, [50 values in nM). High-scoring epitopes were chosen as follows: among top 10 in PickPocket and same epitopes among high-scoring ones in NetCTLpan, so as to find common epitopes to increase accuracy. A total of 12 HLA supertypes present in both algorithms were as follows: HLA-A*01:01, HLA-A*02:01, HLA-A*03:01, HLA-A*24:02, HLA-A*26:01, HLA-B*07:02, HLA-B*08:01, HLA-B*27:05, HLA-B*39:01, HLA-B*40:01, HLA-B*58:01 and HLA-B*15:01 [NetCTLpan v. 1.1  and PicPocket/, ) were us-B*15:01 . For ORF4.3.http://www.cbs.dtu.dk/services/NetMHCIIpan/, [NetMHCIIpan v. 3.2  was useCIIpan/, . The epi4.4.http://tools.iedb.org/immunogenicity/, [Immunogenicity is a characteristic property of peptide epitopes that can elicit an immune response. High binding affinity to HLA alleles is not a sufficient criterion for high immunogenicity. Therefore, all the epitopes that were generated as a consensus were checked for their immunogenicity. IEDB immunogenicity tool  was usenicity/, . For helnicity/,  and ITcenicity/,  were useCombined score:  +  * HLA_score), where alpha is optimized to 0.4.The 7 alleles used are: ‘HLA-DRB1:03:01’, ‘HLA-DRB1:07:01’, ‘HLA-DRB1:15:01’, ‘HLA-DRB3:01:01’, ‘HLA-DRB3:02:02’, ‘HLA-DRB4:01:01’ and ‘HLA-DRB5:01:01’. The whole HTL epitope sequence list belonging to each protein was given as an input, and IEDB-recommended combined method was selected for scoring. Lower combined scores imply higher immunogenicity according to the authors developing this prediction tool. The immunogenic versus non-immunogenic epitopes cut-off was a combined score of 50 as per CD4episcore paper.ITcell works on the basis of three stages of MHC-II processing and presentation pathway. These three stages are, in the authors'  own word4.5.As globally conserved epitopes are relevant at this time to contain and treat coronavirus infection, the clustering approach was used to find patterns among disparate datasets. In order to group epitopes into several clusters, IEDB epitope cluster analysis tool  was appl4.6.https://research.bioinformatics.udel.edu/peptidematch/batchpeptidematch.jsp) of Protein Information Resource was used.All the immunogenic CTL and HTL epitopes obtained were used to search against human proteome data from UniProt database  for any matches to human proteome, thus avoiding cross-reactivity. For this, Multiple Peptide Match tool (4.7.https://www.ebi.ac.uk/Tools/msa/muscle/) tool was used to generate MSAs of all SARS-CoV-2 proteins with corresponding proteins in other HCoV and MERS species. The species chosen and their GenBank accession IDs were: Alpha-CoV: HCoV-NL63 (NC_005831.2), HCoV-229E (NC_002645.1); Beta-CoV: HCoV-OC43 (NC_006213.1), HCoV-HKU1 (NC_006577.2), MERS CoV (NC_019843.3) and SARS-CoV-2 . The spike protein sequence for SARS-CoV was taken from UniProt (P59594). In view of different/unclear annotations, it was difficult to get corresponding protein sequences from SARS-CoV (RefSeq accession ID NC_004718.3). There are no human CoVs in gamma/delta CoV categories. In addition, bat coronavirus RaTG13 sequences (MN996532.1) were also used.MUSCLE  with one part of the manuscript published with 29523.v2  and anot53463.v1 . All the


Prosthetic vascular graft infections of the thoracic aorta are rare but can be fatal. Our comparison of collagen- and gelatin-coated grafts showed that collagen-coated grafts were associated with increased biofilm formation and bacterial adherence in vitro and with higher rates of perioperative vascular graft infections in vivo.  Prosthetic vascular graft infections (PVGIs) of the thoracic aorta occur in 1%–3% of patients, but lethality rates are >20% (Staphylococcus aureus has been shown to colonize rifampin-bonded grafts 7 days after implantation (The few comparative studies reported have focused mostly on use of antibiotic-bonded grafts to reduce the risk for PVGIs in vitro and in vivo (https://www.getinge.com) and gelatin —to biofilm formation. The collagen graft is coated with a highly purified form of cross-linked bovine type 1 collagen. The gelatin graft is coated with a modified mammalian gelatin. Gelatin is derived mainly from type 1 collagen by heat denaturation, a process during which collagen loses its native triple helical structure. The resorption time for collagen is 4–8 weeks and for gelatin, 14 days. For our in vivo study, we investigated the rate of infections associated with the 2 grafts among prospective patients undergoing open-chest cardiac surgery at the University Hospital Zurich .For our in vitro study, we compared the susceptibility of 2 thoracic vascular woven polyester grafts with different coatings—collagen  and in tryptic soy broth  at 37°C. Graft patches were incubated with bacteria in tryptic soy broth–glucose solution (glucose concentration 8 mmol/L) at 37°C for 72 h, and medium was exchanged every 24 h. The patches were washed with phosphate-buffered saline (PBS), sonicated at 44 khz, and the resulting optical density at a wavelength of 600 was measured in a microplate reader. All bacteria, apart from Pseudomonas aeruginosa strain 2, showed increased biofilm formation on the collagen graft compared with the gelatin graft patches  patients or laboratory strains  according to the manufacturer’s instructions. The graft patches were placed in 8-well microslides  and visualized by confocal laser scanning microscopy with a Leica TCS SP8 inverted microscope (https://www.leica-microsystems.com) under a 63×/1.4 oil immersion objective. We selected 2 representative spots per graft patch, providing a stack of horizontally acquired images (512 × 512 pixels representing an area of 244.8 μm × 244.8 μm) with a z-step size of 0.12 μm. We processed the obtained stacks by using Imaris 9.2.0 software . Biofilm height and volume were determined as previously described . The plates were incubated with bacteria at 37°C for 30 min. Bacteria were washed, stained with 0.1% crystal violet , solubilized in 95% ethanol, and the resulting optical density at 570 nm was measured. The tested strains adhered substantially better to collagen  or type B gelatin solution , we used nonparametric tests . When normalized to the total number of control patients (n = 384 who had undergone the cardiac surgery but had no PVGI), the calculated percentage of intracavitary thoracic PVGI (n = 28 VASGRA patients who had undergone the cardiac surgery and had PVGI) was higher for patients in the collagen-graft (10.8%) versus the gelatin-graft group .To assess the effects of these findings in vivo, we analyzed 412 prospective participants with woven polyester grafts: 28 VASGRA participants in whom intracavitary thoracic PVGI developed and 384 contemporaneous open-chest cardiac surgery patients in whom PVGI did not develop (controls) . Data anWe found more biofilm formation on collagen-coated polyester vascular grafts than on gelatin-coated grafts, possibly because the tested strains adhered substantially better to collagen than to gelatin. When we analyzed prospective patients with PVGI and contemporary controls, the percentage of PVGI associated with collagen-coated grafts was also higher.The strengths of our study include use of patient-derived strains of bacteria and the prospective collection of patients with incident PVGIs and controls. Our study has some limitations. First, it was a single-center study, resulting in low patient numbers, and the role of the graft material as a risk factor for PVGI is difficult to prove because of the rarity of the infection. Furthermore, data for patients with PVGI have to be interpreted with caution because some patients have additional foreign material in the heart. Second, publicly available information on the exact type of coating as well as the application procedures used is lacking. In addition, the experiments were performed in a static experimental setup instead of a flow chamber. However, because we were interested in direct bacterial adherence to the graft material, simulating a scenario in which infection would occur as consequence of unintentional inoculation during the perioperative period, we believe that the setup used is adequate. We did not reproduce a gram-positive and gram-negative mixed biofilm formation experiment because a monomicrobial setup enabled us to determine which material and coating was more susceptible to bacterial adherence in a more controllable fashion.In conclusion, biofilm formation was increased on collagen-coated vascular grafts compared with gelatin-coated grafts in vitro. As opposed to another risk factor analysis from the VASGRA study (Additional materials and results for study of polyester vascular graft material as risk factor for intracavitary thoracic vascular graft infection.


Lactobacillus plantarum or heterofermentative Lactobacillus buchneri. Inoculations of the two different inoculants resulted in substantial differences in microbial community and metabolic composition as well as their dynamics in ensiled corn. Inoculants also altered the correlations of microbiota in different manners, and various keystone species were identified in corn silages with different treatments. Many metabolites with biofunctional activities like bacteriostatic, antioxidant, central nervous system inhibitory and anti‐inflammatory were found in the present silage. A constitutive difference in microbiota dynamics was found for several pathways, which were upregulated by specific taxa in middle stage of fermentation, and widespread associations between metabolites with biofunctions and the species of lactic acid bacteria dominated in silage were observed. Multiple microbial and metabolic structures and dynamics were correlated and affected the fermentation process of the corn ensiling systems. Results of the current study improve our understanding of the complicated biological process underlying silage fermentation and provide a framework to re‐evaluate silages with biofunctions, which may contribute to target‐based regulation methods to produce functional silage for animal production.Multi‐omics approach was adopted to investigate the modulation of bacterial microbiota and metabolome as well as their interactions in whole crop corn ensiling systems by inoculating homofermentative  Lactobacillus plantarum or heterofermentative Lactobacillus buchneri. Results of the current study improve our understanding of the complicated biological process underlying silage fermentation, and provides a framework to re‐evaluate silages with biofunctions, which may contribute to target‐based reglation methods to produce functional silage for animal production.Multi‐omics approach was adopted to investigate the modulation of bacterial microbiota and metabolome as well as their interactions in whole crop corn ensiling systems by inoculating homofermentative  This might be due to the higher pH condition that advantages the breeding of microorganism  and 45 days (P = 0.013) compared with control. The enriched L. parabrevis, L. heilongjiangensis and unclassified Lactobacillus, and L. farciminis and L. paralimentarius during 14‐ and 45‐day fermentation of L. plantarum‐treated corn silage, respectively, had strong competitiveness that might account for the decrease in bacteria diversity.Based on full‐length 16S rRNA amplicon sequencing of silage bacteria, an average of 11 948 circular consensus sequencing (CCS) sequences were obtained from each sample. The principal coordinates analysis (PCoA) based on unweighted UniFrac distances and weighted UniFrac distances was applied to identify factors that shape the differences between whole crop corn silage microbiomes (beta diversity). The results indicated a significant bacterial species succession according to fermentation time, while they were indistinguishable among silage inoculated without or with eri Fig. . Howevereri Fig. . InoculaAgrobacterium (6.42%), Microbacterium (6.35%), Sphingobacterium (5.88%), Chryseobacterium (5.05%) and others (31%). After 3 days of fermentation, most bacterial reads were derived from Lactobacillus, Acinetobacter, Klebsiella, Methylobacterium and Citrobacter in all treatments. From 7 to 90 days of fermentation, Lactobacillus dominated the ensiling process. The dominating species were L. farciminis, L. parabrevis, L. brevis, L. parafarraginius, L. heilongjiangensis, L. acetotolerans and L. silagei  effect size (LEfSe) analysis was conducted Fig. . On 3 daL. buchneri, L. parafarraginis, L. hammesii and Agrobacterium larrymoorei in silage without inoculants; L. panis and unclassified Enterobacteriaceae in silage inoculated with L. buchneri; and L. crustorum and Agrobacterium larrymoorei in silage inoculated with L. plantarum can be considered as keystone taxa.Microbial network was used to assess the correlation between various species and to statistically identify the bacteria species that were keystone taxa for modulating the fermentation process. The results indicated that inoculants obviously changed the correlations within microbiota Fig. . The putTo evaluate the changes of metabolome of whole crop corn silage, we used the untargeted metabolomic approach. In total, 643 metabolites were identified Data . The heaL. buchneri were clearly separated by PC2 , while the differences with control were not significant in samples fermented for 90 days  of metabolome showed that the samples inoculated with ays Fig. . The conine Data . At the L. plantarum and L. buchneri modulated the microbial communities, which resulted in marked differences in functional shift. The results indicated that the pathways closely related to silage fermentation were metabolism of carbohydrates, amino acids, energy, cofactors and vitamins and xenobiotics biodegradation and metabolism, and these pathways were upregulated in middle stage (7 to 45 days) of fermentation.In order to determine whether the observed variations in bacterial community succession contribute to community‐wide functional shifts, we used KEGG database with PICRUSt approach Fig. . In compd‐alanine metabolism , middle period  and late period . We observed driving or attenuating functional shifts of flavones and flavonol biosynthesis, polycyclic aromatic hydrocarbon degradation, glycosaminoglycan degradation and ism Fig. .Lactobacillus reactions  in silages with different treatments were clearly exhibited .There were widespread associations between bacteria and well‐predicted metabolites with biofunctions across the silages with or without inoculants Data . The corL. buchneri, L. silagei and L. parafarraginis were positively correlated with lysine, methionine and phenylalanine, while L. plantarum was negatively with the three essential amino acids. In corn silage inoculated with L. buchneri, lysine and methionine amino acids were positively correlated with L. silagei and L. odoratitofui, lysine was also positively correlated with L. acetotolerans, and phenylalanine was only positively correlated with L. silagei. Among these essential amino acids, only phenylalanine was positively correlated with L. silagei and L. parafarraginis while negatively correlated with L. plantarum in corn silage treated with L. plantarum.Essential amino acids such as lysine, methionine and phenylalanine were detected in the present study. In control group, the L. plantarum were positive in corn silages with inoculants, while it was negatively correlated with L. silagei in all treatments. The naringin was also negatively correlated with L. parafarraginis in L. plantarum‐treated and control groups, but it was negatively correlated with L. acetotolerans and L. odoratitofui in the L. buchneri‐treated samples. Metabolite of 3,4‐dihydroxybenzoic acid was negatively correlated with L. paralimentarius and L. heilongjiangensis in control group, and it was also negatively correlated with L. parafarraginis and L. silagei in L. plantarum‐treated samples. However, the 3,4‐dihydroxybenzoic acid was positively correlated with L. plantarum in L. plantarum‐treated samples. Ferulic acid with antioxidant activity was also found in the present study. It was positively correlated with L. pontis, L. heilongjiangensis, L. spicheri and unclassified Lactobacillus in control group but negatively correlated with L. plantarum in L. buchneri‐treated corn silage.Correlations between the metabolite of naringin with bacteriostatic activity and Lactobacillus parafarraginis, L. silagei and L. buchneri were positively correlated with 4‐aminobutyric acid in control group, while L. heilongjiangensis and L. pontis were negatively correlated with it in L. buchneri‐inoculated samples. The linolenic acid was positively correlated with L. parabrevis, L. heilongjiangensis, L. pontis, L. koreensis and L. xiangfangensis in L. plantarum‐treated corn silage (P > 0.88), while no LAB was positively correlated with linolenic acid in samples inoculated with L. buchneri and in control group.L. plantarum while negatively correlated with L. silagei and L. parafarraginis in corn silage inoculated with L. plantarum. There was no LAB that positively correlated with salicin in samples inoculated with L. buchneri and in control silage. L‐malic acid was positively correlated with L. heilongjiangensis in control group, while it was negatively correlated with L. parafarraginis and L. acetotolerans in L. buchneri‐treated samples and was negatively correlated with L. silagei in L. plantarum‐treated corn silage.Salicin was positively correlated with Lactobacillus and negatively correlated with Proteobacteria  were mainly tracked to L. silagei, L. buchneri and L. parafaraginis in control samples, to L. silagei, L acetotolerans, L. odoratitofui and L. panis in samples inoculated with L. buchneri, and to L. silagei, L. parafaraginis, L. kefiri, L. parafaraginis and L acetotolerans in L. plantarum‐treated samples.To further characterize the effects of bacterial species and metabolites on fermentation quality, the correlation analysis between species, well‐predicted metabolites and fermentation quality in different treatments was investigated Fig. . The resria Data . The pH dl‐alanine and oxoproline), carbohydrates (sucrose and ribose), polyphenol (catechol and naringin), alcohols (xylitol and 2‐aminoethanethiol) and 2‐methylfumarate during corn ensiling. Naringin was positively correlated with pH in inoculated samples, while it was negatively correlated with lactic and acetic acids in L. plantarum‐treated samples and was negatively correlated with propionic acid in all treatments. In control group, phenylethylamine, lysine, catechol and tyramine were positively correlated with lactic and propionic acid but negatively correlated with pH. Xylitol was positively correlated with lactic and acetic acids and was also negatively correlated with pH. N‐methyl‐dl‐alanine was positively correlated with propionic acid; 2‐aminoethanethiol was positively correlated with lactic and propionic acids; and ribose was positively correlated with lactic acid. In corn silage inoculated with L. buchneri, lysine and oxoproline were negatively correlated with pH and positively correlated with propionic acid. Salicin was negatively correlated with acetic acid. Sucrose was positively correlated with pH while negatively correlated with lactic and propionic acids. As for corn silage added with L. plantarum, 2‐methylfumarate, tyramine and oxoproline were negatively correlated with pH, positively correlated with lactic, acetic and propionic acids. Lysine was also negatively correlated with pH, and phenylethylamine and xylitol were positively correlated with lactic acid.The fermentation quality was closely correlated with well‐predicted metabolites such as amino acids and derivatives  was identified as keystone taxon in L. buchneri‐treated silage. The abundances of these two species were limited after 3 days of ensiling and disappeared after 45 days of ensiling, whether the silages have worse characteristics or not, and this needs to research further.The role of microbial communities in ecosystem functioning is defined  were predicted to be upregulated in middle stage of fermentation. Although the inoculation with L. buchneri upregulated the flavones and flavonol biosynthesis pathway contributed by Lactobacillus phylotypes, a few flavonoids were detected in the present study.The end‐products during fermentation are either directly produced by microbial activity or indirectly as a result of degradation and transformation of substances present in the material. Plant enzymes in aerobic silo stage  harvested at the stage of half milk‐line was chopped into a particle size of 2 cm using a forage cutter . Three treatments were applied including a control without inoculation and inoculations using Lactobacillus plantarum MTD/1  and Lactobacillus buchneri 40788 . The inoculants were mixed into distilled water and applied at a rate of 1 × 106 cfu g−1 fresh matter (FM), and an equal volume of distilled water was sprayed in the fresh corn for control. The chopped whole crop corn was randomly divided into 57 batches to result in three replicates per treatment and time . Each batch was individually treated with the additives. The batches were then ensiled in vacuum‐sealed polyethylene plastic bags (30 cm × 23 cm) with about 300 g of fresh corn crop per bag. The bags were stored at ambient temperature (22–25°C) and sampled after 3, 7, 14, 30, 45 and 90 days of fermentation.The whole crop corn (2SO4 (7.14 mol l−1) and filtered with a 0.45‐mm dialyser. Lactic, acetic, propionic and butyric acid were analysed by high‐performance liquid chromatography .A 20 g fresh sample and silage were put in a juice exactor and squeezed with 180 ml distilled water for 30 s at a high speed, then filtered via medical gauze with four layers. The filtrate pH was measured with a glass electrode pH meter immediately. A portion of the filtrate of each sample was acidified with HThe DNA extraction of fresh corn crop and silages was performed with a DNA isolation kit  according to the manufacturer instructions. The PCR amplification of the full‐length 16S rRNA gene for SMRT sequencing was carried out.et al., http://www.arb‐silva.de) database (classified at a bootstrap threshold of 0.8) using the Mothur (https://mothur.org/wiki/Classify.seqs) software, the reads belonging to unclassified Lactobacillus were subjected to the best BLAST hit method to gain species level information  and KEGG (http://www.genome.jp/kegg/) commercial databases were used to identify metabolites.Raw peak exaction, data baseline filtration and calibration of the baseline, as well as peak alignment, deconvolution analysis, peak identification and integration of the peak area were performed with Chroma TOF 4.3X software of LECO Corporation and the LECO‐Fiehn Rtx5 database ) and P‐value < 0.05.For statistical analysis, missing values were assumed to be below the level of detection. However, metabolites were detected in all samples from one or more groups but not in samples from other groups, which were assumed to be near the lower limit of detection in the groups in which they were not detected (Theriot Proteobacteria and Firmicutes) and well‐predicted metabolites (similarity > 500) with biofunctions. To further characterize the effects of bacterial species and metabolites on fermentation quality, the Spearman’s correlation analysis between bacterial species, identified metabolites and fermentation quality in different treatments was computed and network plots were performed by Cytoscape (v 3.6.1). In order to show the plots clearly, we screened only part of the data. Briefly, the well‐predicted metabolites were selected with similarity > 500, and then, the absolute value of correlation coefficients of bacterial species and fermentation quality was > 0.7; the absolute value of correlation coefficients of variables of fermentation quality and well‐predicted metabolites was > 0.6; P < 0.05.We computed the Spearman’s rank correlation coefficients for bacterial species and all identified metabolites with biofunctions . We performed heatmap construction as a graph and annotated species by the phylum .Click here for additional data file.Data S2. Relative concentration of detected substances in corn before and after ensiling for 3, 7, 14, 30, 45 and 90 days. Identified and unidentified substances .Click here for additional data file.Data S3. The contribution of 634 metabolites to the first principal component (PC1) and standard error .Click here for additional data file.Data S4. Wilcoxon test statistics for significant functional shifts predicted by FishTaco approach in different tretments .Click here for additional data file.Data S5. Spearman correlation coefficients of that between microbiota and metabolites with biofunctions in corn silage inoculated with L. plantarum . The absolute Spearman.Click here for additional data file.Data S6. Spearman correlation coefficients of that between microbiota, well‐predicted metabolites and variables of fermentation quality in corn silage inoculated with L. plantarum.Click here for additional data file.


This research investigated the viscosity, thermal, thermomechanical, and microstructural properties of potato starch–wheat gluten composite systems with different starch/gluten ratios under mechanical shear and heating conditions. Results showed that the peak, trough, and final viscosities increased with the increase in potato starch fraction. The breakdown and setback values of samples decreased with increasing gluten content, and the endothermic enthalpy showed a similar variation trend. The gelatinization temperature of the samples increased significantly as the gluten proportion increased. Morphological observation showed that the gluten protein was wrapped around potato starch granules and the starch granules have a diluting effect on gluten network. Moreover, gluten formed a water diffusion barrier out of the starch granules, this barrier effect and the competitive hydration between starch and gluten could primarily explain the delayed gelatinization temperatures. The ratio of potato starch to wheat gluten has significant effect on viscosity, thermal, and Mixolab thermomechanical properties of the starch–gluten composites. Potato starch plays a dominant role in upholding paste viscosity, and gluten considerably contributes to the formation of potato starch–wheat gluten composite dough system. Potato is also one of the main raw materials for starch extraction, and the starch content of potato is generally 9%~25%. Both the whole potato flour and the extracted potato starch are widely used in food industry due to their unique physicochemical properties. Studies showed that potato flour (potato starch as main composition) or potato starch supplements significantly influence the dough's processing performance  and the final products quality  , making it difficult to know the effects of starch on gluten network formation. A common simplifying approach in investigations of the role of gluten and starch in dough systems is to use gluten–starch model dough samples (recombine the extracted starch and gluten). This allows precise control of the gluten content and also excludes complex effect of other ingredients in the dough systems . The wheat gluten contained 7.22% moisture, 89.34% protein, 9.82% starch, and 0.82% ash. The production way of the wheat gluten was as follows: Wheat flour was mixed with water and then separated by pumping the flour paste into a series of hydrocyclone. The obtained flow was then washed and sieved to get the wet gluten. After that, a drying process was applied before packing. Moisture, protein, and ash contents were determined using AOAC official methods . Potato starch and wheat gluten were used as control samples. The thermal, microstructural, and thermomechanical properties of control samples and the potato starch–wheat gluten composite systems were studied.2.4The viscosity properties of native potato starch, wheat gluten, and starch–gluten composite systems were analyzed using Rapid Viscosity Analyser . The tests were conducted under fixed shear conditions with a completely controlled temperature cycle of heating, holding, and cooling. This procedure ensures the generation of highly reproducible gelatinization and pasting profiles. Samples (2 g each) were suspended in 25 ml of water to prepare suspensions to be measured by the RVA. The constant rotating speed (160 rpm) and fixed heating up and cooling down process were adopted for the measurement. The heating temperature was maintained at 50°C for 1 min, followed by a ramped‐up temperature to 95°C at a rate of 12°C/min; the temperature was held at 95°C for another 2.5 min and then cooled down to 50°C at the same rate (12°C/min). Finally, the temperature was held again at 50°C for 2 min. The peak viscosity, trough viscosity, final viscosity, peak time, break down, setback, and pasting temperature were recorded during the heating and subsequent cooling process.2.50), peak temperature (Tp), peak width at half height (ΔT), and endothermic enthalpy (ΔH) were calculated automatically. A sealed empty pan was used as reference.The thermal properties of potato starch, wheat gluten, and starch–gluten composite systems were investigated using a differential scanning calorimeter . Samples (3 mg) were weighed into stainless steel pans, and 10 μl of distilled water was added before the pans were hermetically sealed. The pans were equilibrated at 4°C for 12 hr before heating from 25 to 100°C at a rate of 5°C/min by DSC. The onset temperature . The quality of protein network and the starch behavior of dough were analyzed using the standard procedure during heating and cooling. First, the mixture was held at 30°C for 8 min. Second, the temperature was increased to 90°C at a rate of 4°C/min and then maintained for another 8 min. Finally, the temperature was decreased to 50°C at a rate of 4°C/min and held for 10 min. Parameters including water absorption (%), maximum torque (C1), minimum torque (C2), peak viscosity (C3), holding viscosity (C4), final viscosity (C5), protein weakening (C1–C2), breakdown (C3–C4), setback (C5–C4), and gelatinization temperature were obtained from the recorded curve.Mixing and pasting properties of potato starch, wheat gluten, and their mixtures were studied using a Mixolab analyzer . Samples were placed in a bowl with two kneading arms, and the amount of water added was determined by the water absorption capacity of the samples. The torque (Nm) was obtained as a function of time, thus allowing evaluation of the thermochemical properties of dough samples. The Chopin2.7The microstructures of the raw potato starch, wheat gluten, and starch–gluten composite dough samples were observed through field‐emission ESEM . The dough samples used for ESEM observation were obtained using the Mixolab mixing bowl. The blended flour and water were added in the bowl and mixed at a constant temperature of 30°C, and the mixing rate was 80 rpm/min. The amount of added water was determined by Mixolab until the torque produced by the dough reached 1.1 ± 0.05 Nm at 14% moisture basis. The dough samples used for microstructural observation were obtained from the inner part of the dough. The samples were then placed in 3% glutaraldehyde overnight, washed with 0.1 mol/L phosphate buffer thrice, and dehydrated in a graded acetone series  for 20 min. Afterward, the samples were dried and sprayed with gold. Potato starch granules and wheat gluten were used for observation without pretreatment. ESEM was used to observe and photograph the samples at 500× magnification.2.8The data reported were averages of triplicate observations and expressed as mean ± standard deviation. ANOVA and Tukey's test at .05 significance level were conducted to evaluate the significant differences among sample means. ANOVA was performed using SPSS 18.0 .33.1The pasting profiles for potato starch, wheat gluten, and their composite systems at different starch/gluten ratios were examined during heating and cooling periods by RVA. As shown in Figure Breakdown is the reflection of the susceptibility of cooked starches to their disintegration during heating  and peak temperatures (Tp) of the native potato starch were 51.64°C and 56.51°C, respectively, and the endothermic enthalpy was 12.10 J/g. With the increasing proportion of gluten, the onset and peak temperatures increased significantly, whereas the endothermic enthalpy (ΔH) decreased. This finding may be attributed to the reassociation of starch to a certain extent and the gluten addition significantly changed the thermal denaturation process of the complex. The absorption of excess water by gluten interfered with starch swelling and thus delayed the gelatinization process (Champenois, Rao, & Walker, The gelatinization parameters of samples are listed in Table 3.3The thermomechanical properties of samples during mixing, temperature rising, pasting, and subsequent cooling were shown in Figure 3.4The pristine surfaces of the native potato starch granules and wheat gluten were observed through ESEM Figure a and b. Figure 4The ratio of potato starch to wheat gluten has significant effect on viscosity, thermal, and Mixolab thermomechanical properties of the starch–gluten composites. Potato starch plays a dominant role in upholding paste viscosity, and gluten considerably contributes to the formation of potato starch–wheat gluten composite dough system. The ΔH value of the composites decreased significantly with the increasing gluten/starch ratio. The gelatinization temperature of the starch–gluten composite systems increased with the addition of wheat gluten. Wheat gluten enveloped the surface of starch granules and potato starch granules showed a diluting effect on gluten network. The current findings are expected to contribute to the better understanding of the mixing, gelling, and pasting behavior of potato starch–wheat gluten composite systems. Such information is particularly relevant to the development of potato‐based staple foods. For example, the viscosity of potato‐based staple products may increase in the heating process with the increase of potato proportion. Less cooking time may be needed for the potato‐based products with higher potato proportion since higher starch content lead to a decrease of gelatinization temperature. Moreover, a proper proportion of potato starch/flour was suggested in potato‐based staple products since potato starch granules have a diluting effect on gluten network.The authors declare that they do not have any conflict of interest.This study does not involve any human or animal testing.


Mitochondrial DNA maintenance defects (MDMDs) is one of the critical pediatric dysfunction. One of the recent report indicated that a severe patient of MDMDs carries the NP_056528.2:p.Asn221Ser (N221S) variation in the RRM2B gene (NM_015713.5). However, there is no direct evidence demonstrating the nature of the N221S variation.This study aimed to utilize zebrafish and morpholino oligomer (MO) knockdown technique to provide direct evidence for the nature of the N221S variation in the RRM2B.rrm2b in zebrafish and dose‐dependently induced morphological defects. Furthermore, co‐injection of human wild‐type RRM2B mRNA with MO‐e4i4 successfully rescued the developmental defects, whereas co‐injection of RRM2B/N221S mRNA with MO‐e4i4 did not rescue the developmental defects.The results showed that two distinct MOs were both able to perturb the expression of In conclusion, the functional assay in this study provided the direct evidence proving that the N221S variation is a loss‐of‐function mutation and plausibly related to the pathogenic developmental defects found in the infants of previous clinical reports. It might be life‐threatening with mitochondrial malfunction. Mitochondrial diseases originate from pathogenic mitochondrial DNA (mtDNA) mutations that lead to defects in various mitochondrial proteins disrupting the electron transport chain and oxidative phosphorylation. With these dysfunctions, mitochondria are unable to produce sufficient energy in different tissues, especially, in the highly ATP demanding tissues such as cardiac muscle, liver, the renal, and central nervous systems , is decomposed during mitosis. Another form, p53‐controlled RNR small subunit 2 (p53R2) (OMIM: 604712), is maintained throughout all phases of the cell cycle and is encoded by the gene RRM2B in human  is responsible for catalysis of the reduction of ribonucleotide triphosphate to dNTPs by radicals  on chromosome 8 (chr8:103231064hg19) was reported recently  targeted at the junction between intron 2‐exon 3 (MO‐i2e3) and exon 4‐intron 4 (MO‐e4i4), respectively, to knock down the expression of rrm2b in zebrafish. Subsequently, in order to investigate the potential pathogenic effects of N221S variation, we used human wild‐type RRM2B and RRM2B/N221S mRNAs to rescue the impaired zebrafish embryos. Overall, this study aims to provide evidence for the pathogenic effects of the N221S variation on RRM2B gene. We proved that N221S variation on RRM2B gene is a loss‐ofs‐function mutation.The crucial residues for enzyme activity of RRM2B protein are highly conserved across different species  and were performed in accordance with the approved guidelines.2.2The AB wild‐type zebrafish were obtained from Taiwan Zebrafish Core Facility  and maintained at a density of two to four fish per 3‐L tank in the aquatic facility with an automatic circulation system. The culture system was maintained at 28.5 ± 0.5°C under a light‐to‐dark cycle of 14:10 h, and the fish were fed with live adult brine shrimp twice a day  and exon 4‐intron 4 (MO‐e4i4) splicing sites Figure a; additi2.4rrm2b during embryogenesis, the MOs  were delivered to embryos (morphants) by microinjection at 0 hpf. At 24 hpf, the micrographs of morphants were documented . The acquired images were categorized into four classes  according to the severity of morphological defects. Additionally, the different morphological scores for normal, mild, severe, and death were set at 0, 1, 2, and 3, respectively. The score of severity is calculated as the mean of morphological score in each treatment group. The sample size (n) of each group was indicated on top of histogram.To evaluate the importance of zebrafish 2.5To evaluate the cell death, 24 hpf control and MO‐e4i4 (4 ng) morphants were stained with 5 μg/ml acridine orange (Invitrogen) for 5 min followed by three washes with E3 medium. Subsequently, the embryos were subjected to confocal microscopy  immediately. All images were acquired by Z projection. The total dead cells were counted with ImageJ . The synthesized mRNAs were aliquoted, and stored at −80°C. The mRNAs were mixed with 0.5% phenol red immediately before each experiment. For rescue experiment, 100 pg mRNA of target genes were co‐injected with 4 ng MO‐e4i4. For oxidative stress induction, embryos were cultured in E3 medium with or without the supplementation of 0.5 mM H2O2 for 8 h .Total RNA was extracted from zebrafish embryos using TRIzol Reagent  according to the manufacturer's instruction. Ten or 15 embryos in each treatment were collected as a pool for each experiment. The single‐stranded cDNA was synthesized from 2 μg of total RNA with oligo(dT)In order to confirm the perturbation of mRNA splicing, primers flanking exons 2 and 5 were designed , total DNA was extracted from 8 hpf embryos using cell and tissue genomic DNA extraction kit . Briefly, embryos were homogenized and lysed by lysis buffer with proteinase K (1 mg/ml) at 60°C for 30 min. Proteins were removed by adding protein removal buffer followed by centrifugation at 14,000× To quantitatively analyze the expression levels of target genes and mtDNA copy numbers, cDNA, or genomic DNA were mixed with 5 μl iQ SYBR Green Supermix (Bio‐Rad) and 1 μl of primer set mix to a total volume of 10 μl. To amplify the desired fragments of target genes, the reactions were performed at 95°C for 3 min, and then, 39 cycles of 95°C for 3 s and 60°C for 30 s followed by 60°C for 1 min with a thermal cycler . The sequences of primer pairs used in this study are listed in Table 2.9p value less than 0.05 was considered a statistically significant difference.All data were presented as mean ± standard error of the mean (SEM).The statistical analysis was performed using Prism 8 software . The phenotypic penetrance and score were subjected to Kruskal–Wallis test with Dunn's multiple comparisons. The acridine orange stain was subjected to Mann–Whitney test. The qPCR results for mtDNA copy number and gene expressions were subjected to ordinary one‐way ANOVA with Tukey's multiple comparison test with a single pooled variance. A 33.1rrm2b during embryogenesis, we designed two MOs (MO‐i2e3 and MO‐e4i4), targeted at intron 2‐exon 3 and exon 4‐intron 4 splicing site, respectively, to knockdown the expression of zebrafish rrm2b  mRNA  and ROS‐scavenging enzymes and responders  were examined by qPCR. Under oxidative stress, expression levels of nd1 and nd5 were significantly reduced in 8 hpf zebrafish embryos, but the reduction in nd1 level was significantly ameliorated in MO‐e4i4 morphants  in early zebrafish embryos  was significantly increased (Figure 2O2‐treated controls (Figure rrm2b play a critical role in responding to oxidative stress. Similarly, human RRM2B mRNA not only significantly rescued the expression levels of gclc and gstp1 but also further boosted the express of catalase, while both RRM2B/N221S and RRM2B/A61P variants failed to exert similar rescuing effect on the oxidative stress response (Figure rrm2b play a role in mitochondrial homeostasis and oxidative response in early zebrafish embryos just like its counterparts in mammalian cells. Human RRM2B are able to rescue MO‐e4i4 morphants phenotype penetrance in correlation with the mitochondrial homeostasis and oxidative response.Under oxidative stress, a series of transcriptional responses will be triggered. Although the oxidative responders (d Figure . Interess Figure  indicatie Figure . Taken tRRM2B variants are highly related to MDMDs. It is suggested that patients expressing serious lactic acidosis, muscle hypotonia, ataxia, and renal tubulopathy may have RRM2B mutations (Finsterer & Zarrouk‐Mahjoub, RRM2B variant, N221S, has a series of severe MDMDs including hypotonia and lactic acidosis (Penque et al., RRM2B/N221S mRNA still exhibited severe developmental defects and mitochondrial dysfunction (Figures RRM2B gene and the mutations within these regions are highly pathogenic.Recently, accumulating evidence shows that  Figures . These rrrm2b plays a crucial role in zebrafish embryogenesis. With this model, this study provided direct evidence confirming that the N221S variation disrupts the function of RRM2B gene product and the N221S variation is a loss‐of‐function mutation.In conclusion, the present study demonstrated that The authors have no conflict of interest to declare.Yen‐Tzu Tseng performed most of the experiments and participate in the manuscript drafting and revision. Shang‐Wei Li participated in some experiments and data analysis, and drafted the original manuscript. Wei‐Chun HuangFu contributed to the experimental design and manuscript drafting. Yun Yen contributed to the research conception and experimental design. I‐Hsuan Liu contributed to the research conception, experimental design, as well as manuscript drafting and revision. All the authors proofread and approved the submitted manuscript.


Bar  and Cry1c genes  were compared to those of their control lines. The two transgenes are responsible for herbicidal resistance and insect tolerance, respectively. The starch CLDs were measured by enzymatic debranching and measuring the molecular weight distributions of the resulting linear chains. It was found that although all the lines had similar amylose contents, the CLDs of both amylopectin and amylose for Cry1c were noticeably different from the others, having more short amylopectin and long amylose chains. These CLDs are known to affect functional properties, and indeed it was found that the Cry1c transgenic lines showed a lower gelatinization temperature and faster digestion rate than the control or Bar lines. However, a slower digestion rate is nutritionally desirable. Thus, pleiotropic effects from genetic modifications can indirectly but significantly affect the starch synthesis pathway and thus change functional properties of significance for human health.This paper examines if, in maize, starch structure and starch-dependent properties might be altered by pleiotropic effects arising from genetic modifications that are not directly related to starch synthesis. The molecular structure, specifically the starch chain-length distributions (CLDs), of two maize lines transformed with  Genetic engineering is an avenue to improve crop traits such as yield, stress tolerance, and nutrition. Many studies have focused on phenotypic effects (changes in characteristics resulting from interactions between the organism’s genetics and its environment) of the exogenous (introduced) genes, but pleiotropic effects (unanticipated changes arising from the introduced genes) have only occasionally been noted ,2,3,4. PStarch, the main component of cereal endosperm, is the largest single energy source in human food. There are two types of starch molecules, amylose and amylopectin, both with (1→4)-α linear links and 1→6)-α branch points. Amylopectin is a large molecule with a vast number of short branches, while amylose is somewhat smaller, with a few long-chain branches. Amylopectin chains in native starch form double helices with each other in crystalline lamellae, while amylose is located in the amorphous lamellae which form alternating layers in starch granules. Starch molecular structure has a close relation to starch properties, such as gelatinization and digestibility . The am-α branchCry1c gene) and a herbicide-resistant gene . The transformation of the Bar, USA. gene has been applied in soybean, maize, cotton, wheat, and canola  was purchased from Merck KGaA, Darmstadt, Germany. All other chemicals were reagent-grade and used as received.Protease from –1. The finely ground powder was purified with a wet milling procedure following a method described elsewhere [w/v) at 4 ℃ overnight and then homogenized in sodium metabisulfite solution using a homogenizer . The homogenized slurry was stirred with a mixture of NaCl solution (0.1 M) and toluene (9:1 v/v) to remove most lipids and proteins from the maize kernels. The mixture was stirred for 1 h and then allowed to stand until the starch granules settled at the bottom. The toluene layer and most of the NaCl solution layer, containing proteins and lipids, were removed. This procedure was performed several times until the toluene layer was clear. The remainder was repeatedly washed with water and pure ethanol to obtain starch granules, followed by air-drying at room temperature overnight.The maize grains were frozen in liquid nitrogen before being cryoground into powder with a mixer mill  for 2 min at a frequency of 15 slsewhere . Each crw/w) LiBr to yield a final concentration of 2 mg/mL and 4 mg/mL, respectively, prior to SEC analysis.The starch samples were extracted from the maize flour for SEC analysis of starch molecular structures following a method described elsewhere . In briew/w) LiBr was used as eluent with a flow rate of 0.3 and 0.6 mL/min, respectively. Universal calibration was used to convert SEC elution time to the SEC separation parameter, the hydrodynamic radius Rh [6 Da. The SEC weight distribution obtained using a differential refractive index detector, w(log Rh), gives  the total weight distribution (not molecular weight distribution) of molecules as a function of log Rh [Rh can be converted to degree of polymerization  X using the Mark–Houwink equation [The debranched CLDs were characterized using an Agilent 1260 infinity SEC system  with a refractive index detector  following a previously described method . A combiadius Rh , using pf log Rh . For theequation .−1, respectively. An empty sealed pan served as the reference, and indium was used for calibration. Onset temperature (To), peak temperature (Tp), conclusion temperature (Tc), melting temperature range (Tc − To), and melting enthalpy (ΔH) were determined from each endotherm.Thermal properties of purified starch granules from wet milling were measured by differential scanning calorimetry . Starch  was precisely weighed into a crucible with 6 mg of water. The pans were sealed hermetically and allowed to equilibrate for 1 h at room temperature prior to the DSC measurement, followed by a holding step at 20 °C for 1 min. The scanning temperature range and heating rate were set at 20–120 °C and 10 °C min2, 0.49 mM MgCl2, and 0.02% NaN3). The starch suspension was added to an enzyme solution (0.5 mL) containing 12.5 μL of amyloglucosidase and 25 μg of pancreatin in sodium acetate buffer, and the mixture was incubated and stirred at 200 rpm in a water bath at 37 °C. Starch digesta (0.1 mL) were collected at 0, 10, 20, 40, 60, 90, 120, 180, 240, and 300 min, and the digestion was stopped by adding 0.9 mL of absolute ethanol. The digestion kinetics of retrograded starch (g/100 g of dry starch) were determined from the amount of glucose released in the supernatant, measured using the Megazyme D-Glucose (GOPOD Format) Assay Kit, with a conversion factor of 0.9 (the ratio of the molecular weight of the anhydroglucose monomer unit in starch to that of glucose). The in vitro starch digestion procedure was carried out according to a previously described method . Isolatet, C(t):k is the digestion rate coefficient and C∞ is the fraction remaining at long times. Application of the LOS method shows which steps of the digestion kinetics follow first-order kinetics [k) obtained by the LOS equation  were then used as an initial estimation for nonlinear least-squares fitting (NLLS) to obtain more accurate values of k and C∞ [The digestogram was fitted using the logarithm of slopes (LOS) method ,16. Thiskinetics . The ratk and C∞ .X ~ 100. The amylopectin model assumes that enzyme sets, each comprising one starch synthase (SS), starch branching enzyme (SBE), and starch debranching enzyme (DBE), operate concertedly to synthesize a component in the amylopectin CLD. The overall amylopectin CLD is the sum of the contributions of each enzyme set. The parameters in the model are, for the ith amylopectin (Ap) enzyme set, βAp,i, the ratio of the activity of SBE to that of SS (the activity of DBE is constrained by certain requirements and is implicit in those of SS and SBE), and hAp,i, the relative activity of SS. For SEC CLD data (where some features of the fine structure are masked by band broadening), the amylopectin CLD can be fitted by three enzyme sets, denoted i, ii, and iii, and the relative contributions of enzyme set ii and iii to enzyme set i, hAp,ii and hAp,iii.The CLDs in the amylose and amylopectin regions were fitted with the amylose model of Nada et al.  and the βAm,i and hAm,i, with the same meaning as those for amylopectin [An amylose CLD usually presents distinct features (given good SEC separation) in the form of several maxima or shoulders. These features are associated with different enzyme sets, and the fitting parameters are lopectin .p < 0.05.All measurements were performed in duplicate. All data are reported as mean ± standard deviation and analyzed by Minitab 16  with analysis of variation (ANOVA). The significant difference of the mean values was determined at X, are given in Bar lines and control lines were very similar. Although the amylose content of the three lines was not statistically different, the proportion of the chains with intermediate length  in Cry1c lines was lower than the others, which can also be observed in The weight CLDs of endosperm starch from the maize lines with different genetic background, as functions of DP To, Tp, Tc, (Tc-To), and ΔH of retrograded starches from the different lines are shown in Cry1c samples compared with the others, which could be partly due to the influence of the difference in short (DP 6–12) amylopectin chains in Cry1c starch, as reflected in the different values of βAm,i (see below). The other thermal parameters from the two transgenic starches did not show significant differences.The values of k and the fraction remaining after long-time hydrolysis, C∞, were found between Cry1c and the other two lines; the analysis used two bioreplicas for each transgenic line and each replica had two technical repeats.As shown in Cry1c were significantly lower (p < 0.05) than the others, while the βAp,i values of Cry1c were significantly higher (p < 0.05). A higher value of βAp,i in Cry1c lines means a higher ratio of the activity of SBE to that of SS in Bar and Control lines, which is related to the synthesis of the single-lamellae spanning chains (DP 6–33), dominated by enzyme set i. No significant difference was observed in the βAp,iii values of any of the transgenic lines and control lines, which shared a similar ratio of enzyme set iii activity, which dominates synthesis of the two-lamellae spanning chains (DP 34−67). The parameter hAp,i is the relative contribution of enzyme set i to the entire amylopectin CLD. The difference for enzyme set i was more significant than that of enzyme set iii, indicating that the proportion of long amylopectin chains in Cry1c samples was lower than the others, due to the distinctly different activities of enzyme set i. The lower contribution of enzyme set iii  was observed in Cry1c lines compared with the others. Details of the various components in the fitting process are given in the βAm,i for Cry1c and the other two lines, which is for amylose region i (DP 10−350). The amylose CLD data were best fitted with three distinct enzyme environments (regions). The parameterization results are given in βAm,i values of region 1 and region 2 correlated negatively with the digestion rate coefficient. The amylopectin and amylose models give independent starch structural parameters correlating with the in vitro digestion rate. The amylose content and amylopectin CLD fitted parameters showed no significant difference between the samples; for amylose, the The objective in this paper was to see if there are variations in structurally related functional properties such as digestibility and thermal properties between the transgenic lines and control lines. Certain structural changes are known to affect some functional properties, for reasons discussed in the literature  and herbicide-resistant gene (Bar gene), both of which are unrelated to genes controlling starch synthesis [Cry1c lines have lower gelatinization temperature and faster digestion rate.The pest-resistant gene  were foCry1c were one of the factors accelerating the digestion rate [Cry1c lines during amylopectin synthesis, since the values of βAp,ii and βAp,iii were both higher than in the other lines. SBEII is able to transfer shorter chains (DP ≤ 12) than SBEI, which participates in amylopectin synthesis rather than amylose synthesis [Cry1c lines. The changes in structural features also could have arisen from lower SS activity. There are three types of SSs with multiple isoforms. SSs are responsible for elongating (1→4)-α-glucan chains of amylose and amylopectin. The shortest chains of amylopectin are the preferred substrates for SSI, while SSII is believed to be responsible for intermediate-length chain synthesis (DP 12–24). SSIII is most abundant in tubers, and responsible for long amylopectin chains (DP > 30). The CLD fitting parameters quantify the starch CLDs, with the parameters from the model fitting being enzyme activity ratios and thus reflecting genetic differences. The altered starch enzyme activity could be the consequence of somaclonal variations (genetic variation in plants generated from somatic cells cultured in vitro), triggered by the callus regeneration [Since the samples were all cooked, and thus could be digested quite quickly by α-amylase, some of the starch would have been degraded into reducing sugars during the sampling process, which is why starch digestion did not start at 0% in the digestogram. This phenomenon is commonly found among cooked starchy food digestion measurements . The LOSion rate . The strynthesis . SBEIIb ynthesis . The higneration . Bar and Cry1c transformed lines. No significant difference was found in amylose content, but the Cry1c lines had noticeably different molecular structures from the Bar and control lines: fewer short amylose chains and more long amylopectin chains. This is similar to a previous study [Cry1ab, regulated by Ubi promoter, might influence starch properties, including reduced viscosity; we suggest here that this is due to the type of pleiotropic effects on starch molecular structures.The present study examined starch molecular structure, thermal properties, and digestibility of retrograded starch from us study  showing Cry1c lines, in terms of nutritional value, may be less desirable than the Bar and untransformed lines, since higher starch digestibility is associated with type II diabetes, colorectal cancers, and obesity. This manuscript focuses on seeing if there can be alterations in starch structure among transgenic maize lines where the transgenes are not supposed to affect starch biosynthesis. Because a change is seen in starch structure, it shows that it is possible to have deleterious effects on starch structure where the genetic alterations should have had no such effect. Seeing if the transgene insertion is close to genes involved in starch biosynthesis would help understand the mechanism for the observation and point the way to avoiding the problem in the future. The likelihood of pleiotropic effects on starch molecular structure and properties should be considered along with crop improvement when creating transformed plants. The observation that commonly used transformations, which were not expected to have any effect on starch structure, in fact in one case had a significant effect, fulfills the aim of this paper. The mechanism whereby this occurred is of interest, and merits future investigation.Genetic modification in non-starch-related genes has been shown here to be able to lead to alterations in starch structures and properties, in particular, the gelatinization and digestibility properties studied here. In this case, the starch harvested from


The rapid Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV2) outbreak caused severe pandemic infection worldwide. The high mortality and morbidity rate of SARS CoV2 is due to the unavailability of vaccination and mutation in this virus. The present article aims to design a potential vaccine construct VTC3 targeting the non-mutational region of structural and non-structural proteins of SARS CoV2.In this study, vaccines were designed using subtractive proteomics and reverse vaccinology. To target the virus adhesion and evasion, 10 different structural and non-structural proteins have been selected. Shortlisted proteins have been screened for B cell, T cell and IFN gamma interacting epitopes. 3D structure of vaccine construct was modeled and evaluated for its physicochemical properties, immunogenicity, allergenicity, toxicity and antigenicity. The finalized construct was implemented for docking and molecular dynamics simulation (MDS) with different toll-like receptors (TLRs) and human leukocyte antigen (HLA). The binding energy and dissociation construct of the vaccine with HLA and TLR was also calculated. Mutational sensitivity profiling of the designed vaccine was performed, and mutations were reconfirmed from the experimental database. Antibody production, clonal selection, antigen processing, immune response and memory generation in host cells after injection of the vaccine was also monitored using immune simulation.Subtractive proteomics identified seven  proteins of this virus that have a role in cell adhesion and infection. The different epitopes were predicted, and only extracellular epitopes were selected that do not have similarity and cross-reactivity with the host cell. Finalized epitopes of all proteins with minimum allergenicity and toxicity were joined using linkers to designed different vaccine constructs. Docking different constructs with different TLRs and HLA demonstrated a stable and reliable binding affinity of VTC3 with the TLRs and HLAs. MDS analysis further confirms the interaction of VTC3 with HLA and TLR1/2 complex. The VTC3 has a favorable binding affinity and dissociation constant with HLA and TLR. The VTC3 does not have similarities with the human microbiome, and most of the interacting residues of VTC3 do not have mutations. The immune simulation result showed that VTC3 induces a strong immune response. The present study designs a multiepitope vaccine targeting the non-mutational region of structural and non-structural proteins of the SARS CoV2 using an immunoinformatic approach, which needs to be experimentally validated. Immuno-pathogenesis of the infectious epidemic COVID-19 emerged as serious intimidation worldwide. In the Coronaviridae family, among four different coronavirus classes , alpha and beta positive-sense RNA virus strains have been confirmed for broadly epidemic infection . Severe Among SARS CoV2 genomic RNA, 66% codes for the non-structural or essential proteins, and 33% codes for the structural or accessory proteins. Non-structural proteins have a significant role in virus replication and transcription in the host cell, while structural proteins cover the outer surface and participate in the host evasion system to cause the infection. SARS CoV2 mutation prone  genomic To overcome the issues such as cost and time associated with traditional method , of disease prevention , the virIn the present study, non-mutational sequences of SARS-CoV2 were targeted to design a multiepitope vaccine construct. SARS-CoV2 proteome was investigated to identify antigenic proteins and different T-cell and B-cell epitopes were identified in selected proteins, and their antigenicity, allergenicity and physiochemical properties have been evaluated. The molecular docking of final epitope constructs was performed with different TLRs and HLA alleles to confirm the stable binding interaction of the multi-epitope vaccine-receptor complex. Vaccine constructs were further assessed for its cross-reactivity and immune response in humans, as well as their similarity with the human microbiome.https://www.ncbi.nlm.nih.gov/). These proteins are ORF6 protein (YP_009724394.1), membrane glycoprotein (YP_009724393.1), ORF3a protein (YP_009724391.1), nucleocapsid phosphoprotein (YP_009724397.2), ORF10 protein (QHI42199.1), ORF7a protein (YP_009724395.1), envelope protein (YP_009724392.1), ORF1ab (YP_009724389.1), ORF8 protein (QHD43422.1) and surface glycoprotein (YP_009724390.1). All FASTA sequences were used as an input for further immuno-informatics analysis . AllergenFP  class I molecules supertype representative , and predicts the 8, 9, 10 and 11 mer peptides to reduce the experimental efforts. With the help of the neural network, the algorithm server has predicted promiscuous high binding affinity nonameric peptides . HLA binlergenFP  and ToxilergenFP .Immunogenicity prediction (IEDB) confers the property which can elicit the cellular and humoral response in the host cell against viral infection. Shortlisted NetCTLpan epitopes were used for immunogenicity prediction that confers the property which can elicit the cellular and humoral response in the host cell against viral infection. Promiscuous epitopes ORF3a protein (one epitope), surface glycoprotein (two epitopes) and ORF1ab polyprotein (17 epitopes) were used as input peptides for immunogenicity prediction. High binding capacity epitopes (by IEDB immunogenicity tool server) were selected as positive immunogenicity epitopes. This server predicted the immunogenicity level based on the epitope positions in the expected peptide and physicochemical properties of an amino acid .With the help of the IEDB MHC II binding prediction tool, T helper cell epitopes were predicted. In vaccine development, the vaccine must cover most of the world’s population. Hence to overcome this HLA alleles variation, a reference set has been used that includes the panel of 27 alleles, which covers the >99% of the population . IEDB MHB cell epitopes detect viral infections by an antibody-based immune response. IEDB BEPIPRED  and ABCphttp://crdd.osdd.net/raghava/ifnepitope/).The comparative evaluation of all the finalized MHC I, MHC II and B cell epitopes has been done to remove the overlapping epitopes. Non-overlapping epitopes should have a unique presence in the virus. To minimize the cross-reactivity in host cells, non-overlapping epitopes were BLAST against human proteome (ID 9606) using Protein Information Resource . BesidesAll screened epitopes that contain the antigenic property with no allergenicity, toxicity and cross-reactivity have been finalized to design the chimeric multi-epitope vaccine construct against SARS CoV2. A potent vaccine should activate the immune response in the host cell but not activates the detrimental immunity. Hence, to maintain the balance of immunity in the host cell, half non-IFN gamma inducible peptides have been selected, and vise-versa. Epitope binding with B and T cell receptor needs a degree of freedom. Based on the linker’s length, flexibility and rigidity, EAAAK and GGGS linker have been used. EAAAK linkers rigidity is used to maintain spaces between proteins domain while GGGS linkers provide flexibility to construct with minimum linker-epitope interference to maintain the epitope function .http://raptorx.uchicago.edu). The modeled vaccine was refined by GalaxyRefine server and validated by PSVS analysis, ProSA , allergenicity (via AllergenFP) and toxicity (via Toxinpred). Vaccine constructs physicochemical behavior analysis is the major key to find out the post-injection symptoms. A highly antigenic vaccine construct  with lower allergic and toxicity has been further evaluated by the Protparam Server . The webs, ProSA  and QMEAs, ProSA  per publhttp://hdock.phys.hust.edu.cn/)  and HLA alleles via molecular docking using PatchDock server . The docedu.cn/) The Molecular Dynamics Simulation (MDS) analysis was performed by Desmond using the OPLS3e force field and TIP3P solvent. MDS was run for 50ns in duplicate as per published methods . In brieThe binding affinity as well as dissociation constant of the VTC3 vaccine construct with the HLA and TLRs were further estimated at different simulation time periods using the PRODIGY server . The MDSE-value ≤ 10−5) and identity ≥40%   identifiity ≥40% . For furMAESTRO web server  was usedhttp://kraken.iac.rm.cnr.it/C-IMMSIM/). This server is based on the Celada-Seiden model that predicts the immune  stimulation against vaccine construct (Multi epitope vaccine immune simulation profile was performed using C-ImmSim online server (onstruct . The simhttp://www.jcat.de/) was utilized for codon optimization of VTC3 genes in a prokaryotic organism like E. coli. The E. coli K12 strain was selected to enhance the expression efficiency of VTC3. The rho-independent transcription terminators, prokaryotic ribosome binding sites, and cleavage sites of some restriction enzymes were avoided. Sites for restriction endonuclease HindIII and BamHI were added to the N and C terminals of the VTC3 gene, respectively, and subsequently cloned between HindIII and BamHI site of pET28a (+) vector using the SnapGene 4.2 tool (https:/snapgene.com/) to ensure the in-vitro expression.The amino acid sequence of VTC3 was reverse translated to DNA. Codon optimization is important for cloning and expression of VTC3 genes. The Java Codon Adaptation tool  did not get any potent HLA binder peptide. The rest six proteins showed the peptide binders with different HLA supertypes. From this server results, we have identified different epitopes ORF8 (eight epitopes), ORF7a protein (nine epitopes), envelope protein (four epitopes), ORF3a protein (three epitopes), surface glycoprotein (125 epitopes) and ORF1ab polyprotein (707 epitopes) binders. From the results, we manually screened peptides that showed a binding affinity with more than one HLA allele. This approach will minimize the HLA polymorphism so that promiscuous peptides will show binding to HLA of the wide population. After the manual screening of proteins, we have shortlisted ORF8 (one epitope), ORF7a protein (two epitopes), envelope protein (two epitopes), ORF3a protein (three epitopes), surface glycoprotein (43 epitopes) and ORF1ab polyprotein (277 epitopes) epitope binders. Based on antigenicity, allergenicity and toxicity analysis of peptide, different epitopes of ORF8 (zero epitopes), ORF7a protein (zero epitopes), envelope protein (zero epitopes), ORF3a protein (one epitope), surface glycoprotein (two epitopes) and ORF1ab polyprotein (17 epitopes) were further shortlisted, and the potential epitopes were selected that can enhance immune response via HLA activation .Immunogenicity prediction of ORF3a protein (one epitope), surface glycoprotein (two epitopes) and ORF1ab polyprotein (17 epitopes) epitopes had shown the positive immunogenicity score of ORF3a protein (one epitope), surface glycoprotein (one epitope) and ORF1ab polyprotein (six epitopes) epitopes . The posHelper T-cell mediated 15 amino acid extended epitopes were generated against the HLA allele reference set. In results, the percentile rank 0.1 was set as the threshold to filter the HLA interacting epitopes binding affinity. Based on reference threshold, ORF8 (five epitopes), ORF7a protein (zero epitopes), membrane protein (zero epitopes), envelope protein (zero epitopes), ORF3a protein (zero epitopes), surface glycoprotein (19 epitopes) and ORF1ab polyprotein (18 epitopes) showed <0.1 percentile rank . Low perUsing the IEDB Bepipred server, different epitopes from selected proteins like ORF8 protein (two epitopes), ORF7a protein (two epitopes), membrane glycoprotein (one epitope), envelope protein (one epitope), ORF3a protein (one epitope), surface glycoprotein (28 epitopes) and ORF1ab protein (98 epitopes) have been screened. With ABCpred server-based B cell epitope analysis, the epitope of ORF8 protein (nine epitopes), ORF7a protein (seven epitopes), membrane glycoprotein (one epitope), envelope protein (three epitopes), ORF3a protein (two epitopes), surface glycoprotein (50 epitopes) and ORF1ab protein (20 epitopes) was shortlisted. To filter out the common epitope from both servers, manual screening has been done to shortlist the common overlapped epitopes. This selects different epitopes from Orf8 protein (two epitopes), ORF7a protein (two epitopes), membrane glycoprotein (one epitope), envelope protein (one epitope), ORF3a protein (one epitope), surface glycoprotein (16 epitopes) and ORF1ab protein (eight epitopes). These epitopes were selected for the further experiment . The scrAll finalized MHC I, II and B cell epitopes were used for comparative analysis  to removZ-score of −3.35 and QMEAN of −10.75  and TLR4  at 10 ns simulation time. This showed good interaction between VTC3 with HLA and TLR1/2. The binding affinity and dissociation constant at different simulation times  was cloned into a pET28a vector between the HindIII and BamHI .In the present study, a multiepitope vaccine constructs VTC3 for SARS CoV2 have been proposed with the help of reverse vaccinology that compiles the outer surface-exposed epitopes of the structural and non-structural proteins of this virus. There are different therapeutic strategies, and ongoing research has been tried to control SARS CoV2 , 2020a. + T cell-mediated HLA allele  unique interaction with immune dominant peptide contributes as a potential to control and prevent viral infection . It has been observed that the TLRs mediated virus interaction not-only combat virus virulence and infection but also sometimes initiate the host system to overturn downstream signals for the benefit  of the virus-cell. During the viral infection, membrane-associated proteins interaction with TLR2 and TLR4 plays a nuanced role in exceeding inflammatory responses via adhesion and invasion that vitiate the host cell . Simultanfection . The intThe high mortality and morbidity rate of COVID 19 is unprecedented due to the unavailability of vaccination; hence effective treatment strategies , rapid development, trials and production are needed immediately for this global pandemic disease. To reach out the success, it is necessary to evaluate all possible vaccine candidates to find out the one viable outcome. To increase the chance of success, WHO initiated vaccine solidarity trials to test all vaccine candidates until they fail. In the present study, an attempt was made to design a multi-epitope vaccine against SARS CoV2 that targets its exposed peptides of structural and non-structural proteins. Immunogenicity, allergenicity, toxicity and potent IFN-gamma inducer scores have also been analyzed to narrow down efficient epitopes further. Peptide matching with the human proteome showed no indication of possible cross-reactivity. However, current reverse immuno-informatics approaches were executed to target surface-exposed proteins for enhancing effective host innate with humoral and cellular immune responses. The present study concludes the design of VTC3 as a multiepitope vaccine against SARS CoV2.10.7717/peerj.11126/supp-1Supplemental Information 1Click here for additional data file.


Reff) [et al. that it is essential to calculate the Reff by using the next generation matrix (NGM) approach. Actually, we also commonly used the NGM approach to calculate the reproduction number of other infectious diseases [We reviewed with interest Zhao's letter regarding our article exploring the approach of calculating the effective reproduction number (Reff) . We entidiseases .Reff from the NGM approach instead of a simplified equation in our study [f, daily br and daily dr were 0.0003 (0.03%), 2.46 × 10−5 and 1.24 × 10−5, respectively, which were much lower than those of ω (1/5), γ (1/14) and γ’ (1/21), respectively. We also calculated the values of Reff by using the simplified equation we used and the two equations provided by Zhao et al., and we found that they were almost the same (We did not provide the complex equation of ur study , becausethe same .Fig. 1.Therefore, we agree to use an accurate approach to estimate the transmissibility of an infectious disease. However, a simplified equation would be easier to be performed by the primary public health department than a complex one.


We assess the expected long-run consequences of the unfolding COVID-19 pandemic and use these as a platform to argue that international business (IB) as a field should expand its research agenda to study the international division of labor. The worldwide response to the COVID-19 pandemic is accelerating the shift toward the de-globalization of capital, but it will also speed up the move to a stronger globalization of labor. This paradoxical, simultaneous occurrence of de-globalization and globalization offers rich opportunities for future IB research. At the time of the final drafting of this Commentary in January 2021, the COVID-19 crisis was still unfolding. Many countries that went into some form of lockdown in the spring of 2020, and stepwise liberalized their economies after the virus seemed under control, have had to reintroduce new lockdown measures because of localized new virus outbreaks. And countries that initially abstained from taking strong measures are now forced to act. Whatever the timing of the measures, the number of people infected with the new variant of the coronavirus continues to increase globally, as does the related number of deaths. Vaccines are coming, but vaccination campaigns take time to roll out. In the meantime, the virus mutates into new and more contagious variants.On the economic front, 2020 has seen an unprecedented contraction of GDP in most countries across the world, and the outlook for 2021 is highly uncertain, at best. The IMF  and international economics literature, we predict that, for foreign direct investment (FDI), for trade patterns, and, more generally, for the In this Commentary, we focus mainly on the international division of labor. We briefly develop a number of arguments to support the claim that the COVID-19 pandemic will lead to structural changes in the international division of labor. Our arguments are by no means the ‘final word’ on the issue, but are meant to inform fellow researchers, and also to provide some guidance to practitioners. In doing so, we will focus on two key elements. First, the COVID-19 crisis will disrupt the way international economic activities are organized across countries and firms. Second, the international “within-organization” impact of COVID-19, as an outcome of crisis practices, is that WFH will increase structurally. What does this mean in practice for the international division of labor?First, pandemics such as COVID-19 will strengthen the ongoing trend towards automation and the robotization of work. This implies that the COVID-19 disruption will further stimulate the process of labor-saving technological change. This process will unfold globally. And to the extent that COVID-19 responses give rise to re-shoring or de-globalization, this will mainly involve re-shoring of production and not so much of jobs per se. Second, the WFH trend fueled by the COVID-19 crisis will not necessarily benefit large segments of the labor force in the OECD countries. The currently imposed WFH reveals that many service-related tasks, conventionally considered as non-tradable or non-offshore-able, can actually be performed anywhere, just like manufacturing jobs that were offshored and outsourced. This will unlock the potential for many new jobs and tasks to be performed by workers in emerging market countries, triggering a major global shift in labor demand.Overall, the COVID-19 crisis might induce structural changes in the international economy that work against the production factor ‘labor’ as such, and particularly so for workers in developed countries. The title of our contribution, “Robots do not get the virus”, is meant to reflect this prediction. The COVID-19 crisis will make it more likely that firms across the world will accelerate the introduction of labor-saving production techniques such as robotization. This means that, in terms of the international division of ‘labor versus capital’, adaptation to crises such as the COVID-19 pandemic will favor the latter. In addition, within the context of the international division of labor, new automation techniques that make jobs and tasks less location-dependent are more likely to favor workers in emerging market economies. Our view is that the international economy will be fundamentally reshuffled, with wide-ranging consequences for countries, firms, and workers.Below, we explore the consequences of the COVID-19 pandemic for labor as a ‘factor’ across the world. In IB, attention to labor-as-a-factor is relatively limited, as the focus is traditionally on the firm, and therefore, in classic economics’ jargon, on capital. This does not imply that the study of labor has remained absent in IB. For instance, there is a rich scholarly body of work on expatriates. However, such work is largely positioned in the realm of human resource management (HRM), rather than international labor studies. The latter focuses on analyzing the labor market as an institution. We take the current COVID-19 disruption as our platform to argue that IB would benefit from adopting the international labor market perspective, to complement the international HRM angle. Our broader claim is that IB as a field would benefit from studying labor as a ‘factor’ or ‘market’, or as an ‘institution’ or ‘system’, in addition to addressing HRM issues.We recognize that some of the value-added of IB research results from its multidisciplinary nature. In the realm of ‘division of labor’ issues, insight from other disciplines could be included. For instance, industrial relations and labor sociology could contribute much that is of relevance from an IB perspective. In this Commentary, however, we focus only on the contribution of international labor economics.Zaheer  argued tInternational economic activity brings potential benefits (such as increased cost efficiencies and access to new knowledge or markets), which have to be weighed against the inherent ‘liability of foreignness’. This basic trade-off is a cornerstone of both the IB and international economics (IE) literature, as it helps to determine whether a firm should actually engage in international economic activity. The contemporary IE literature, with its emphasis on the roles of firm heterogeneity, ownership, and institutional differences, in addition to the role of physical distance, has conceptually moved closer to the field of IB than was the case in the past  revolution that took off in the 1990s made it possible to geographically separate the various stages in the production process itself. Various production stages became trade-able and also market-able. In line with Buckley , BaldwinAgainst this background, the first question is whether global value chains have been affected by the COVID-19 pandemic. And, related to this, has the liability of foreignness changed? If so, what are the possible implications for the international division of labor? Our answer to the first question is that the COVID-19 crisis has forced firms to re-assess the risks of their international economic activities, since the perceived liability of foreignness has increased. Producing in various international locations (across multiple continents), and being dependent on specialized value chains, may thus have increased risks because of international dependencies. The Peterson Institute for International Economics  will attribute greater value on geographically closer and more reliable production processes , re-assessing just-in-time delivery, and allowing for increased slack and inventory build-up. It could also imply re-locating to countries with similar institutions and policy preferences. Whatever the precise outcome of this re-assessment, it is hard to escape the conclusion that the liability of foreignness will be affected by the COVID-19 crisis in the foreseeable future. More specifically, the liability of foreignness will, Note that the COVID-19 shock could be seen as merely intensifying an already existing trend. The world had become more uncertain even before COVID-19 entered the stage. In 2017, a global trade war involving the United States and China started to unfold, and weakened the WTO. In 2016, citizens in the UK decided to leave the EU by voting in favor of ‘Brexit’, which the present Conservative government is now implementing. And the European Monetary Union might face another Euro crisis in the aftermath of COVID-19, as also occurred during the financial crisis of 2008-9, with one key issue being the ability of southern European countries to repay their debts. In addition, a number of climate scientists have suggested that COVID-19 is only one example of the type of disruption that can be expected to increase in frequency and intensity in the coming decades. For instance, climate change could bring more extreme weather events, and possibly also stimulate the development of yet unknown infectious diseases. Based on the above, it could thus be argued that COVID-19 only added to the already increasing liability of foreignness. However, because the current pandemic does so very saliently, being a very visible and harsh attack with immediate effects on our way of living, this additional disruption may well push the world economy toward structural change.Assuming that the liability of foreignness, and hence the costs of distance, will not only temporarily (in the midst of the 2020 COVID-19 crisis) but also structurally increase, what could then be the main implications for the international division of labor? At first sight, any tendency to re-shore production would appear to be good news for relatively low-skilled workers from firms in OECD countries, and would similarly be bad news for (less-skilled) workers in China and other (former) emerging market economies. The associated higher production costs in the OECD segment of the world economy would need to be balanced against the lower risks of value chain disruption.However, there are a number of problems with the expectation that re-shoring would increase employment in OECD countries. The first problem is that a pandemic such as COVID-19 provides a strong incentive for labor-saving technological change  will to a substantial degree persist after the COVID-19 pandemic wears off, structurally increasing the share of this work practice because of the perceived benefits to workers and organizations  might increase productivity further and also serve the social purpose of work. On the other hand, many workers and managers may have learned that more tasks can be done remotely, away from the organization and in an effective fashion, than contemplated before the crisis. This conclusion may hold in sectors such as educational services, professional, scientific, and technical services, finance and insurance, and wholesale trade. To a lesser extent, it may also be valid for at least some tasks in industries such as manufacturing, transportation, construction, retail trade, agriculture, forestry, fishing and hunting, and food services. In the context of modularizing global value chain activities, WFH may trigger a (further) fine-slicing of tasks across industries.The Globotics Upheaval, that the rise of the ICT-driven knowledge economy will make workers engage less with tangible capital (“things”) and more with intangible capital (“thoughts”). This implies that the specific physical location for performing such work will become less important. The decoupling of the formal workplace from where work is actually performed is likely to affect the future of work  research papers at