Diospyros digyna and wild D. rekoi trees, sampled seasonally in Mexico in 2014, were analyzed. Metabolic fingerprints revealed higher metabolite diversity in D. rekoi leaves. The TLC bands characteristic of glycosylated flavonoids, predominant in this species, matched the detection of quercetin and quercetin 3-O-glucuronides by liquid chromatography (UPLC-MS) of spring leaf extracts (LEs). Further gas chromatography (GC-MS) analysis revealed abundant fatty acids, organic acids, and secondary metabolites including trigonelline, p-coumaric, and ferulic and nicotinic acids. Phenolic-like compounds prevailed in D. digyna LEs, while unidentified triterpenoids and dihydroxylated coumarins were detected by UPLC-MS and GC-MS. A paucity of leaf metabolites in leaves of this species, compared to D. rekoi, was evident. Higher antioxidant capacity (AOC) was detected in D. digyna LEs. The AOC was season-independent in D. digyna but not in D. rekoi. The AOC in both species was concentrated in distinct TLC single bands, although seasonal variation in band intensity was observed among trees sampled. The AOC in D. digyna LEs could be ascribed to the coumarin esculetin. The LEs moderately inhibited phytopathogenic bacteria but not fungi. Leaf chemistry differences in these Mesoamerican Diospyros species substantiated previous variability reported in tree physiology and fruit physical chemistry, postulated to result from domestication and seasonality.Leaves of semi-domesticated  Diospyros spp.) trees, known as “Tlilzapotl” in the Nahuatl language, which is still relevant in certain regional habitats where they still flourish [The abundant plant diversity characteristic of Mexico represents a potentially rich source of secondary metabolites having bioactive properties. Unfortunately, a significant part of indigenous knowledge about their various beneficial effects is believed to have been lost as the Spanish domination gradually consolidated ,2. The iflourish . Diospyros genus, where more than 20 different species are found, mostly in tropical and subtropical climes, but also sporadically in temperate, mountainous regions [Diopyros species are endemic to it, D. digyna Jacq. excels for its fruit production, due partly to a domestication process and more organized cultural practices. Fruits are not only consumed fresh, but are used in the elaboration of juice, ice creams, jellies, alcoholic beverages, and certain traditional foods, such as “moles”. The latter has contributed to their worldwide commercialization as an “exotic” fruit [Diospyros species and which has been validated by a growing body of experimental evidence [D. rekoi Standl., although considered to be equally or more savory than D. digyna fruits, are collected from trees growing in the wild, usually by shepherds and other itinerant people .Mexico represents an important region of diversity for the  regions . Trees o regions . In westc” fruit , sought evidence ,9,10,11.Diospyros plant secondary metabolites for a diversity of purposes. Flavonoids, polyphenols, phenolic acids coumarins, anthocyanins, terpenes, tannins, and naphthoquinones, isolated from practically all its organs, have been shown to have possible antitumor, analgesic, anti-inflammatory, antiviral and, antioxidant properties, among others [Diospyros species has been scarcely studied. Nevertheless, similar to other better-studied species, such as D. kaki [Multiple studies have concentrated on the study of g others ,11,12,13g others , followeg others , the phyDiospyros species: D. digyna and D. rekoi. Similar to previous reports describing significant differences in tree physiology [D. rekoi trees compared to those of domesticated D. digyna. This finding suggests that the domestication process in D. digyna reduced the metabolic richness of their leaves without affecting important nutraceutical traits, such as antioxidant capacity. In addition, the leaf chemistry was affected by seasonality in a species-specific way. The above results also imply that wild Mesoamerican species, including not only D. rekoi but possibly members of the D. salicifolia complex [D. digyna not only as a source of fruits but of medicinal leaves, as well, and the in situ conservation and commercial exploitation of D. rekoi and other undomesticated Mesoamerican species. This study represents part of an ongoing investigation to determine the influence that domestication, seasonality, growing habitat, and cultural practices, or the lack thereof, have on the physiology and metabolism of two Mesoamerican ysiology  and fruiysiology , the pre complex  represenDiospyros tree species sampled in different locations of western Mexico during a 16-month interval that included the duration of 2014 [D. rekoi trees sampled in the spring of 2014, although their gradual decrease in intensity observed later in the year was accompanied by a greater metabolite diversity (D. digyna LEs was less diversified and did not show evident season-related variations in abundance or complexity (D. rekoi LEs (D. rekoi spring LEs but accumulated from the summer onwards (D. digyna LEs (High performance thin layer chromatography (HP-TLC) was initially used in this study to define the phytochemical profile and antioxidant activity of leaves of two contrasting  of 2014 . Based o of 2014 ,12,13, tiversity . The metmplexity . The usemplexity b permittekoi LEs , mostly  onwards . A blue gyna LEs  which prD. digyna LEs , significantly accumulated to higher levels in spring LEs of D. rekoi. In addition, GC-MS analysis of LEs from each season of 2014 supported the above findings by showing a higher abundance and diversity of metabolites in D. rekoi LEs compared to D. digyna  were also more abundant in D. rekoi LEs which also accumulated distinct short chain FAs that were absent in D. digyna.Total soluble phenol (TSP) content was significantly higher in gyna LEs a and rem species b. A comp the PCA  and S-Pl the PCA . Highly . digyna . Seasona. digyna . SpeciesD. digyna and D. rekoi described above  in the summer was more akin to those characteristic of D. dygina LEs, with a strong signal corresponding to a blue-band phenolic compound migrating very near the solvent front (Rf ≥ 0.9) and a weakened intensity of the prominent orange–yellow bands characteristic of D. rekoi LEs  was significantly higher in D. digyna LEs, except in the spring. The significantly higher AOC detected in spring D. rekoi LEs, in contrast to equivalent LEs from the other seasons, was in accordance with their significant TSP and TF accumulation (D. rekoi LEs by HP-TLC-DPPH (D. digyna LEs tended to be more intense in the spring and winter seasons (The results shown in mulation . LikewisTLC-DPPH a were st seasons b. The in seasons .Diospyros leaf extracts (results not shown), while a moderate activity against phytopathogenic Gram-positive and Gram-negative bacteria was observed in D. rekoi and D. digyna LEs (Clavibacter michiganensis (Cmm) was apparently species- and season-specific, since inhibitory activity was only observed in extracts obtained from spring and summer LEs derived from D. rekoi and D. digyna trees, respectively.No antifungal activity against two known phytopathogenic species was detected in gyna LEs . Growth Diospyros species were clearly different. While LE fingerprints of D. rekoi showed great band diversity and seasonal variability, those from D. digyna were more homogeneous and were less influenced by seasonality. Although less evident, a certain degree of leaf metabolic variability in the trees sampled was also observed. A previous study implied that domestication of D. digyna led to the production of larger and more symmetrical fruits, in addition to a divergence from D. rekoi fruits in several other physicochemical properties [D. digyna leaves herein reported. This difference lends supports to the oft-disputed argument that domestication may lead to a loss of genetic diversity [The HP-TLC metabolic fingerprints generated by LEs of two contrasting operties . This coiversity ,20 and iiversity , tomato iversity , sweet piversity , wheat [iversity , and maiD. rekoi) or evergreen  leaf persistence habit and/or as a response to more stressful conditions faced by D. rekoi trees in contrast to the more controlled conditions in which D. digyna trees were cultivated. Seasonal changes in temperature, photoperiod, and/or water and nutrients availability recorded in the contrasting sampling sites could have been additional factors influencing leaf metabolism in leaves of D. digyna and D rekoi (see below). In this respect, the accumulation of abundant organic acids in LEs of D. rekoi coincided with copious experimental evidence linking plant organic acid metabolism with tolerance to environmental stresses and other detrimental ambient factors, including soil nutrient deficiencies [Diopsyros tree species could have been instrumental for their distinct seasonal changes in plant metabolite profiles [D. rekoi LEs have been reported before in oak [Geranium sylvaticum [Likewise, field experimental data  suggesteciencies . Other oprofiles . Emblemae in oak ,28 and Glvaticum .Diospyros species, which were localized in the Rf ≈ 0.2–0.8 range was reminiscent of data from previous HP-TLC analysis of LEs of pharmaceutically relevant plants [D. rekoi LEs. It also coincided with the chemical composition of D. kaki leaves, where quercetin was found to be one of the main chemical constituents [D. rekoi leaf extracts, comparable to an unidentified and intense band (Rf ≈ 0.22) formerly reported in cultivated and wild garlic leaf extracts [D. rekoi and, to a lesser degree, in D. digyna LEs [D. rekoi LEs which was in correspondence with the high proportion of p-coumaric and ferulic acids in the phenolic composition of D. kaki leaves [D. kaki phenotypes, whose AOC was similarly analyzed using the FRAP and DPPH methods [D. digyna fruits [D. kaki fruits [D. digyna LEs biotic factors, such as growing conditions, temperature, light, nutrients, water, etc., in addition to differential responses to these factors observed among species or cultivars, have on the chemical composition of plants. Such changes directly impact the abundance of secondary metabolites known to have protective and/or beneficial uses for humans [Diopyros species [D. rekoi and D. digyna LEs, have been reported as possible antibacterial compounds, although the weak effect observed could have been due to the absence of non-polar naphthoquinones, considered to have high antibacterial activity [D. digyna and D. rekoi LEs was contrary to a number of reports noting antifungal activity in Diospyros extracts of diverse nature and origin [Diospyros species, considering that several phenolic compounds have been found to be effective against fungi and yeast, presumably by disrupting mitochondrial oxidative phosphorylation [The defined season- and species-specific anti-observed  suggestsr humans . An illur humans . On the  species ,13,55,56activity ,58. The d origin ,59,60. Arylation . This apD. digyna and D. rekoi trees per sampling site, respectively, were obtained in two different locations in western Mexico as previously described [Clavibacter michiganensis subsp. michiganensis (Cmm), Arista strain, was generously provided by A. Alpuche . It was grown in yeast–dextrose–agar . The Petri dishes were incubated at 28 °C until the surface was completely covered by a continuous bacterial film. On the other hand, the Gram-negative Pseudomonas syringae pv. tomato strain DC3000 (Pst) was kindly provided by Alejandro Peñaloza . Pseudomonas syringae pv. tomato was maintained on King’s broth media [Fusarium oxysporum f. sp. ciceris, generously donated by Ernestina Valadez-Moctezuma,  and Colletotrichum gloeosporiodes (ATCC MYA 456), donated by Juan José Peña Cabriales . Both isolates were cultivated on potato dextrose agar for 96 h at 25 °C in the dark. When required, spore suspensions of both phytopathogenic fungi were prepared, in 0.01% Triton X-100, from sporangia harvested from 10 day cultures maintained at 28 °C.Leaf samples from five individual escribed . Samplinth media  supplemeth media . Aliquotth media . Petri dDiospyros leaves were flash frozen in liquid nitrogen as described in Reference [D. digyna and D. rekoi trees sampled in each season of 2014, were pooled together into a single sample and analyzed as described below.eference . Foliar Diospyros species analyzed. Both assays were performed following a modified procedure [Aqueous MeOH leaf extracts separated by HP-TLC were utilized to obtain metabolic fingerprints and to identify the antioxidant-active bands present in the leaf extracts of the two rocedure  of the orocedure . The metrocedure . Three TThe TSP and TF contents in leaves were determined as described previously by Maranz et al.  and SakaIn vitro antioxidant activity in MeOH leaf extracts was measured by means of the 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and ferric ion-reducing antioxidant power (FRAP) assays, respectively, according to the methodologies described by Yahia et al. . Semi-quD. digyna and D. rekoi leaf extracts was obtained by direct-injection electrospray ionization mass spectrometry (DIESI-MS) of aq. MeOH extracts as described previously [D. digyna and D. rekoi aq. EtOH leaf extracts collected in each season of 2014 (GC-MS) and aq. MeOH extracts obtained from leaves sampled in the spring of 2014 (UPLC-MS) were performed. The GC-MS analysis was performed using a DB1MS UI capillary column  fitted to a 7890A gas chromatograph coupled to a selective mass detector (Agilent Technologies). The separation conditions were the following: initial oven temperature of 70 °C, kept for 5 min and then increased to 280 °C at a rate of 5 °C/min. The injector temperature was 230 °C and the mobile phase used was helium gas flowing at a rate of 1 mL/min. Compound metabolite identification was performed using the deconvolution AMDIS program  and the NIST MS Database, search version 2.0. Three technical replicates per leaf extract were included in the analysis.An untargeted metabolomic analysis of more than 900 different ionizable molecules obtained from eviously . Additio18 2.1 m × 150 mm, 1.7 µm; column thermo-stated at 40 °C. Sample injection volumes were 10 μL. Elution was performed at a flow rate of 0.3 mL/min with gradient separation progressing as follows: mobile phase A: de-ionized water containing 0.1% formic acid; mobile phase B: acetonitrile, containing 0.1% formic acid. The elution was isocratic for the first minute at 99% A: 1% B. Then, a 35 min linear gradient increase to 100% B was executed, followed by a 5 min hold at this concentration and a return to the initial 99% A: 1% B conditions in 5 min, for column re-equilibration. The mass spectrometer comprised an orthogonal QTOF Synapt G1 (Waters) operated under the following conditions: electrospray ionization in positive mode, capillary voltage at 3.0 kV, cone voltage 46 V, extractor voltage 4.0 V, with source and desolvation temperatures of 120 °C and 300 °C, respectively. Cone and desolvation gas flow were nitrogen at a flow rate of 20 L/h and 800 L/min, respectively. Leucine-enkephalin (M + H)+ = 556.2771 was infused at a flow rate of 5 μL/min and at a concentration of 2 ng/mL during data acquisition as an internal mass standard to correct for mass drift.For UPLC-MS analysis, aq. MeOH extracts were dried under vacuum and reconstituted in a mixture of acetonitrile/de-ionized water  and filtered through a 0.2 μm filter. Compounds were separated on an Acquity Class I, UPLC System  using a CSH CDiospyros leaf extracts. Briefly, Petri dishes prepared with the appropriate media were uniformly inoculated with a standardized concentration of the test microorganisms . Three sterile Whatman #1 filter paper discs, 1 cm in diameter, and impregnated with 50, 100, and 200 µL of the respective leaf extracts were placed symmetrically on the agar surface. A fourth control disc contained 60% aq. MeOH only. Then, the Petri dishes were incubated under suitable conditions . Biological activity was determined by measuring the capacity of the diffused solutions to inhibit growth of the test microorganism. The extent of the antimicrobial activity was equivalent to the diameter of the inhibition haloes.An agar disk-diffusion method  was empln = 3). The antioxidant activity was subjected to an a posteriori Tukey test to determine the statistical significance of the data at a p = 0.05 level. Three technical replicates of pooled D. digyna and D. rekoi spring leaf extracts were analyzed by UPLC-MS as described above. Data were first imported into Progenesis QI , for automatic alignment, normalization, deconvolution, and compound pre-identification over all sample runs. Compounds were putatively annotated by using Chemspider Databases that comprised an online search using PlantCyc, Plant Metabolic Network, KEGG, and ChEBI. Additional data were produced by targeted MS/MS of several features found relevant by statistical analysis  responsible for leaf AOC, appeared to be species-specific. The higher AOC detected in D. digyna LEs may have been due to the accumulation of esculetin, known to be a very efficient scavenger of free radicals. The AOC was dependent on the season, particularly in D. rekoi, and varied among individual trees. Contrary to other Diospyros species, LEs of these Mesoamerican species had limited to nil antimicrobial activity.This study indicated that, compared to Diospyros species. Increased knowledge about these marginal species could reveal further metabolic traits that could be utilized for the improvement of commercial Diospyros species, such as D. kaki. In addition, it might promote a more organized and rational exploitation/conservation of wild and semi-domesticated Mesoamerican Diospyros species.The information herein reported should stimulate a more profound analysis of these two highly contrasting species, together with other poorly known Mesoamerican


Prevotella copri strongly correlates with RA in previously untreated new-onset rheumatoid arthritis (NORA) patients. Metagenomic assembly of P. copri from NORA patients and healthy controls suggests genetic differences between P. copri from each group. In order to test the hypothesis that genetic differences in P. copri from arthritis patients promote arthritis, I am performing genomic comparison of primary P. copri isolates from NORA patients and healthy controls, and analysis of the immune response to P. copri in mice. Mice colonized with P. copri have increased susceptibility to DSS-induced weight loss and death compared with uncolonized controls. Future experiments will assess the local and systemic immune response in P. copri-colonized, DSS-treated mice. If this work is successful, then it may be possible to exploit genetic variation in P. copri. This could lead to new biomarkers for human disease or even insight into drug metabolism. METHODS/STUDY POPULATION: To validate a strategy to screen for the presence of P. copri in feces, qPCR primers were designed to amplify 8 regions across the 3.5 Mb P. copri reference genome using NCBI PrimerBlast. Primers were validated with DNA from feces for which P. copri abundance was previously determined by 16S rDNA sequencing. P. copri genome-specific primers were used to screen bacterial isolates from NORA patients and healthy controls. The 16S V3-V4 region was sequenced and compared with the P. copri reference 16S sequence to confirm >97% similarity. Genomes of 2 NORA patient isolates were sequenced on Illumina MiSeq, and sequences were compared with the reference genome. A strategy was developed to colonize mice with P. copri: 3-week-old C57BL/6 mice were treated with antibiotics in drinking water for 2 weeks, then switched to water for 2 days before oral gavage with P. copri; 6–7 days after inoculation, P. copri colonization was assessed by plating feces from inoculated mice, and by qPCR of fecal DNA with P. copri-specific primers. A systemic immune response to P. copri was assessed by microbe-specific ELISA for IgG and IgA in the sera of colonized mice. RESULTS/ANTICIPATED RESULTS: P. copri was detected in the stool of 20% of healthy individuals and 50% of NORA patients. P. copri was isolated form 4 healthy individuals and 6 NORA patients. Whole genomes of 96 primary isolates from NORA patients and healthy controls will be sequenced on the Illumina HiSeq platform, and their genomes will be assembled and compared using Spades software. For 2 P. copri isolates for a NORA patient, 89% of 250 bp reads aligned >95% to the P. copri reference genome. Mice can be colonized with P. copri gavaged at >106 CFU. P. copri-specific IgG and IgA were detected in the sera of colonized mice. DISCUSSION/SIGNIFICANCE OF IMPACT: Several primary isolates of P. copri have been collected from healthy controls and NORA patients, which will enable whole genome comparison of these isolates. For the 2 P. copri isolates sequenced, 89% of 250 bp reads aligned >95% to the P. copri reference genome, indicating variability between NORA patient P. copri strains and the P. copri reference genome. The establishment of colonization of mice with P. copri will allow further characterization of the immune response to P. copri at steady state and under pro-inflammatory conditions. Further, the systemic immune response to P. copri indicates that this microbe may have potential to play a role in systemic disease.OBJECTIVES/SPECIFIC AIMS: Rheumatoid arthritis (RA) is one of the most prevalent systemic autoimmune diseases. It is caused by a combination of genetic and environmental factors. In humans, the intestinal microbe


Structural variation (SV) plays a pivotal role in genetic disease. The discovery of SVs based on short DNA sequence reads from next-generation DNA sequence methods is error-prone, with low sensitivity and high false discovery rates. These shortcomings can be partially overcome with extensive orthogonal validation methods or use of long reads, but the current cost precludes their application for routine clinical diagnostics. In contrast, SV genotyping of known sites of SV occurrence is relatively robust and therefore offers a cost-effective clinical diagnostic tool with potentially few false-positive and false-negative results, even when applied to short-read DNA sequence data.We assess 5 state-of-the-art SV genotyping software methods, applied to short-read sequence data. The methods are characterized on the basis of their ability to genotype different SV types, spanning different size ranges. Furthermore, we analyze their ability to parse different VCF file subformats and assess their reliance on specific metadata. We compare the SV genotyping methods across a range of simulated and real data including SVs that were not found with Illumina data alone. We assess sensitivity and the ability to filter initial false discovery calls. We determined the impact of SV type and size on the performance for each SV genotyper. Overall, STIX performed the best on both simulated and GiaB based SV calls, demonstrating a good balance between sensitivity and specificty.Our results indicate that, although SV genotyping software methods have superior performance to SV callers, there are limitations that suggest the need for further innovation. With the continuous advancement of sequencing technologies, our understanding of the importance of structural variation (SV) is increasing . SV playde novo detection of SVs are still in their infancy, with some procedures reporting high (up to 89%) levels of false discovery  , 22 callWe assessed 5 SV genotypers: DELLY , Genome Overall, they can be divided into groups that support only two SV types  up to methods that support all SV types (SVTyper and DELLY) but require specific meta-information. In the following, we give a brief description of each method that we assessed. Further insights can be obtained from their respective publications or manuals.DELLY  is origiGenome STRiP  genotypeSTIX , which iSVTyper  uses a BSV2  uses a sTo first assess the performance of genotyping methods for SVs, we simulated data sets with 100 bp Illumina-like paired-end reads. Each data set includes 20 homozygous SVs simulated for a certain SV type  and a certain size range . For each of the data sets, we called SVs using SURVIVOR , and LumWe discovered only 17 false-positive calls after the initial SV discovery. This low number of false-positive results is in contrast to reports from other studies. However, here we are using simulated data that do not take into account the complexities involved in regions of SVs and other sequencing biases. Interestingly, while this simulated data set represents an ideal case, we still missed ∼17.25% of the simulated SVs.The generated VCF files were taken as input for the 5 SV genotyper callers: DELLY, Genome STRiP, SV2, STIX, and SVTyper. Fig. Interestingly, we observed that certain methods require a specialized VCF file with information provided specific to one SV caller. For example, while SVTyper is able to genotype deletions, inversions, and duplications, it will work on BND (translocation) events only if the ID pairs provided by Lumpy are included in the VCF file. Additionally, DELLY, which is capable of inferring deletion, inversion, duplication, and translocation types of SVs, is only able to genotype deletions if using a standardized VCF without the extra information.The overall performance of each method was evaluated on the basis of the input VCF generated by SURVIVOR. Thus, if all of the short-read–based SV callers were not able to resolve the insertions of 5 kb, then they would be assessed as a “wrong/missed” SV.First, we assessed the ability of the SV genotypers to correctly genotype SVs. SVTyper (64.70%) had the highest rate of correctly genotyping SVs to be present, followed by SV2 (41.57%). Importantly, SV2 was able to genotype deletions and duplications, while SVTyper assessed deletions, duplications, and inversions. Genome STRiP had the lowest (14.40%) success rate of all methods because it can only genotype deletions and duplications. This result was expected because Genome STRiP was designed primarily for population-based genotyping. SVTyper improved marginally (86.26%) when BND events, which represented translocations, were ignored, followed by the next best method SV2 (83.15%) when focused on deletions and duplications. Furthermore, we also benchmarked the SV genotyping methods on their performance, given the truth set . The difNext, we assessed the ability of the SV genotypers to reduce the rate of false-positive results, i.e., initially wrongly inferred SVs. This represents the scenario of accidentally genotyping an SV that is not represented in the sample due to sequencing or mapping biases. Over the 32 call sets, SURVIVOR had only 17 false-positive calls for the simulated data. Genome STRiP performed best in filtering out all falsely detected SVs but had the lowest ability to genotype SV variations. STIX performed better because it could filter out 13 (76.4%) of the false-positive SV calls. In contrast, STIX also achieved a higher (71.76%) performance for correctly identifying SVs. Although SVTyper had the most accurately genotyped SVs, it filtered out fewer false-positive results (70.59%) obtained during the discovery phase.In summary, we observed that none of the methods were clearly superior for correctly genotyping and correctly filtering/non-reporting SV variation. Strikingly, none of the programs were able to genotype insertions or translocations in the simulated data sets. Nevertheless, STIX and SV2 showed strong performance, with a good balance of sensitivity and ability to correctly discard false-positive results.de novo assemblies based on these technologies, alone or in combination )  to obtaiWe obtained the GIAB SV call set (v0.5.0) , the GIAGigaScience Database, GigaDB [Data sets and scripts were deposited in the , GigaDB . We obta, GigaDB , the GIA, GigaDB , and the, GigaDB  from theGIGA-D-19-00035_Tables.xlsx.de novo calls based on SURVIVR Supplementary Table 1. Results for SV discovery set over 32 simulated data sets using SV Supplementary Table 2. Results for SV discovery set over 32 simulated data sets using the ground truth.Supplementary Table 3. Runtime of the different SV genotypersSupplementary Table 4. Size distributions of genotyped SV based on GIAB v0.5Supplementary Table 5. Agreement of genotypes per SV genotyper for GIAB v0.5 predictionsgiz110_GIGA-D-19-00035_Original_SubmissionClick here for additional data file.giz110_GIGA-D-19-00035_Revision_1Click here for additional data file.giz110_GIGA-D-19-00035_Revision_2Click here for additional data file.giz110_Response_to_Reviewer_Comments_Original_SubmissionClick here for additional data file.giz110_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giz110_Reviewer_1_Report_Original_SubmissionDavid Quigley -- 2/28/2019 ReviewedClick here for additional data file.giz110_Reviewer_2_Report_Original_SubmissionRyan Layer -- 3/19/2019 ReviewedClick here for additional data file.giz110_Reviewer_2_Report_Revision_1Ryan Layer -- 7/22/2019 ReviewedClick here for additional data file.giz110_Supplemental_TablesClick here for additional data file.bp: base pairs; BWA: Burrows-Wheeler Aligner; CPU: central processing unit; GATK: Genome Analysis Toolkit; Genome STRiP: Genome STRucture In Populations; GIAB: Genome in a Bottle; kb: kilobase pairs; PacBio: Pacific Biosciences; SNP: single-nucleotide polymorphism; SNV: single-nucleotide variant; STIX: STructural variant IndeX; SV: structural variation;.F.J.S. has participated in PacBio and Oxford Nanopore sponsored meetings over the past few years and has received travel reimbursement and honoraria for presenting at these events.This research was supported by a National Institutes of Health award (UM1 HG008898).V.C. and F.J.S. performed the analysis. All authors wrote the manuscript. F.J.S. and R.A.G. directed the project.


Caenorhabditis elegans (C. elegans) is a well-characterized metazoan, whose transcriptome has been profiled in different tissues, development stages, or other conditions. Large-scale transcriptomes can be reused for gene function annotation through systematic analysis of gene co-expression relationships. We collected 2101 microarray data from National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO), and identified 48 modules of co-expressed genes that correspond to tissues, development stages, and other experimental conditions. These modules provide an overview of the transcriptional organizations that may work under different conditions. By analyzing higher-order module networks, we found that nucleus and plasma membrane modules are more connected than other intracellular modules. Module-based gene function annotation may help to extend the candidate cuticle gene list. A comparison with other published data validates the credibility of our result. Our findings provide a new source for future gene discovery in C. elegans. Caenorhabditis elegans and its gene functions [C. elegans with a relatively small sample size; for example, the 553 samples reported by Kim is the largest sample size to date [High-throughput transcriptomics technology has been extensively applied to investigate the mechanisms of gene regulation. A promising strategy to find the gene functions of unknown genes is the gene co-expression method, which infers gene functions by similar gene expression patterns. This method has been used to explore the global, temporal, and spatial expression of unctions ,2,3,4,5. to date . Althoug to date ,7. ThereMicroarray is a mature high-throughput method for genome-wide gene expression profiling. Thousands of microarray data have been deposited in public databases, however, most individual research uses differential expression analysis methods to find significant changes in expression, ignoring the inherent gene-gene expression correlation. Gene co-expression networks facilitate constructing a global view between genes . WeighteC. elegans microarray data from different experimental conditions. Genome-scale modules of co-expressed genes with clear functional annotations were identified. Module-based qualitative analysis revealed that modules were associated with diverse biological functions. Module-based gene expression variation analysis suggested potential basal or conditional modules. Five modules that may correlate with molting were identified, and candidate cuticle genes were indicated. Those modules were also compared with previous publications to confirm the validity of our results.In this research, we applied WGCNA to publicly available C. elegans Genome Array data were included. Briefly, 151 datasets with 2101 C. elegans samples were downloaded. Detailed information for these datasets is provided in Microarray datasets were obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database under the platform number GPL200. For simplicity, only Affymetrix C. elegans Genome Array Raw cel data were processed in Affymetrix Expression Console software  using the MAS5 algorithm. Microarray data analysis was performed using R software  and Bioconductor WGCNA package  [Microarray datasets were obtained from NCBI GEO database under the platform number GPL200. For simplicity, only Affymetrix .tar.gz) . Briefly.tar.gz) . For eac.tar.gz) . The pow.tar.gz) . Genes w.tar.gz) . Each mo.tar.gz) . Thus, MConnectivity for genes in each module was calculated by the softConnectivity function. Connectivity is a measurement of the sum of the gene expression correlation with all other genes. Genes with high connectivity in a specific module tend to be hub genes, which may play vital roles in module function. Module stability was tested by the average correlation between the original connectivity and the connectivity from half of the samples that were randomly sampled 1000 times. The process was run for every module.C. elegans genome array. In DAVID, an over-representation of a term is defined as a modified Fisher’s exact p-value with an adjustment for multiple tests using the Benjamini method. Other enrichments were performed by inputting a gene set into WormBase to find annotated terms that are over-represented using tissue enrichment analysis (TEA) and phenotype enrichment analysis (PEA) [www.ncbi.nlm.nih.gov/pubmed/) [Gene ontology (GO) enrichment for network modules were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID)  with theis (PEA) . Modularis (PEA) . The stapubmed/) .For gene expression variation analysis, gene expression relative standard deviation for each gene in a module were calculated and the average values for each module were provided.C. elegans [There are several early papers that tried to elucidate the transcriptome in  elegans ,6,18,19.A total of 48 co-expressed gene modules were identified . A repreThere are several modules with same biological process. Ten modules are correlated with embryo development, three modules are correlated with ion transport, two modules are correlated with proteolysis, two modules are correlated with immune response, and two modules are correlated with reproduction. However, these were genes located on different chromosomes or expressed by different tissues. Further, tissue specific gene enrichment analysis revealed that these modules were associated with different tissues .As we have reduced the transcriptome data complexity by gene co-expression modules, we analyzed the gene expression variation at the module level. The gene level relative standard deviation (RSD) of gene expression was calculated, then module level RSD of gene expression was obtained by averaging the RSD of all genes . SortingModules can be relatively independent units which perform a biological function. Associating the modular gene expression with experimental conditions may help to discover a module’s functioning in specific conditions . For exaC. elegans have a short life cycle of about three days at 22 °C. The cuticle protects C. elegans from environmental threats and allows growth by molting. It is synthesized five times, once in the embryo and subsequently at the end of each larval stage prior to molting [ molting . Interes molting .p = 4 × 10−16). It has been shown that aging is associated with a decline in the activity of PMK-1 p38 mitogen-activated protein kinase pathway, which regulates innate immunity in C. elegans [pmk-1 mutant is reduced four-fold by wounding, but the effect is compromised by inhibiting bacterial proliferation [C. elegans (p = 4 × 10−82 and 2 × 10−6) [blmp-1 mutants have a dumpy phenotype, a weak cuticle sensitive to oxidative stress, and show defective distal tip cells (DTC) migration [To seek how these modules affect phenotypes, the transcription factor targeting enrichment was analyzed by WormExp based on curated and high-quality gene expression datasets . These f elegans . While,  elegans . The lifferation . Thus, t × 10−6) . Indeed,igration . p value (7 × 10−7), nine modules were identified to be associated with a specific chromosome region. Four of the molting related modules were associated with a chromosome region, including darkslateblue, honeydew1, magenta, and paleturquoise -Like extracellular protein, Cuticlin-1, and several hypothetical proteins. The hub gene is er larva . Another cuticle . These r cuticle .p = 2 × 10−7, t test). To observe the organization between these modules, the network of modules was also analyzed. These modules can form a higher-order network with 11 meta-modules . Global To check the relationship between these 11 meta-modules, a clustering diagram was plotted showing these modules can be divided into two main branches . The lefC. elegans, and identified 43 sets of highly correlated genes [To validate our results, multiple publications results were compared. Kim constructed a gene expression map for ed genes . They idC. elegans and found that sperm-enriched and germline-intrinsic genes are nearly absent from the X chromosome [Reinke analyzed the global profile of germline gene expression in romosome . We idenhttp://spell.caltech.edu:3000) [http://www.functionalnet.org/wormnet) [To compare our candidate gene list with those predicted by the online function prediction tools SPELL   and Wormwormnet) , the corwormnet) ,19. GeneC. elegans, which identified six major WGCNA modules [p < 5 × 10−302, hypergeometric test), which comprise about 57% of our module genes. Another recent research finding is the transcriptome analysis of the developmental stages of the two sexes in  modules . All sixhttp://bioinformatics.fafu.edu.cn/shiny/sample-apps/celegans/A table containing all the module genes and their function annotation description information was provided in C. elegans transcriptome studies are limited by their sample size and specific conditions. Although recently scientists began to use state-of-art technologies, such as RNA-Seq and fluorescence activated cell sorting (FACS), to try and analyze the sex-, cell-, and stage-specific gene expression, 10 and 40 samples were profiled in the two studies [C. elegans transcriptome data, the largest to date, and identified 48 co-expressed gene modules. These modules include genes for embryo development, cuticle, RNA processing, translation, ion transport and other biological processes. After identifying the gene modules, we further detected the associations between modules and experimental conditions, which may help to identify important modules in a specific condition. The five cuticle modules were subjected to gene prediction. Additionally, the higher order module organization analysis helps to illustrate the relationship between these functional units. Finally, our results were compared with previous studies to establish confidence. Previous  studies ,6. This  studies . Here, wC. elegans transcriptome, facilitating candidate gene screening in future experimental research for biologists.However, some limitations should be considered in the future studies. Technically, there are several parameters that can be adjusted according to data type and research purpose, but currently no standard guideline has been established for parameter setup. These parameters include multiple dataset integration, gene expression data normalization methods, similarity measures, and clustering methods. Biologically, the WGCNA presume that the relationships between genes are approximately linear, nevertheless, the reality is more complex . Gene ex


The state of Rondônia (RO) is a hot spot for human cases of cutaneousleishmaniasis. Many sandfly species in RO are putative vectors ofleishmaniasis.Leishmania DNA and blood meal sources of sandflies inRO. This study examines the diversity patterns and the presence of A sandfly survey was performed between 2016 and 2018 in 10 municipalitiescategorised into three different environment types: (i) Conservation Unit(CUN) - comprised of preserved ombrophilous forests; (ii) Forest Edge (FE) -small forest fragments; and (iii) Peridomicile (PE) - areas arounddwellings.Psychodopygus davisi , Nyssomyia antunesi ,Trichophoromyia auraensis  andTrichophoromyia ubiquitalis . Diversity was thehighest in CUN, followed by the FE and PE environments. One pool ofPs. davisi tested positive forLeishmania braziliensis, reinforcing the possibilitythat Ps. davisi acts as a vector. Thecytochrome b (cytb) sequences were used to identify threeblood meal sources: Bos taurus, Homosapiens and Tamandua tetradactyla. A total of 73 species were identified from 9,535 sandflies. The mostabundant species were  Our results demonstrated that sandflies can switch between blood mealsources in differing environments. This study enhances the knowledge of thevector life cycle in RO and provides information relevant to leishmaniasissurveillance. Leishmania Ross , which causes cutaneous leishmaniasis (CL) and visceral leishmaniasis(VL) in humans.Phlebotomine sandflies  are small insects that act as naturalvectors for protozoans of the genus Bichromomyia flaviscutellata(Mangabeira), Bichromomyia olmeca nociva (Young & Arias),Migonemyia migonei (França), Nyssomyia anduzei(Rozeboom), Nyssomyia antunesi (Coutinho), Nyssomyiaumbratilis (Ward & Fraiha), Nyssomyia whitmani(Antunes & Coutinho), Psychodopygus complexus (Mangabeira),Psychodopygus davisi (Root), Psychodopyguswellcomei , and Trichophoromyiaubiquitalis (Mangabeira), might be involved in the transmission ofLeishmania that cause CL.Of the 280 sandfly species found in Brazil, 13 species are the proven vectors ofleishmaniasisNyssomyiaintermedia, Nyssomyia neivai,Nyssomyia shawi,Psychodopygus carrerai, Psychodopygus hirsutushirsutus-Trichophoromyia auraensis (Mangabeira).Leishmania (Leishmania) infantumNicolle is the causative agent of VL, and its primary vector is Lutzomyialongipalpis (Lutz & Neiva), which is distributed throughoutBrazil.Le.(Le.) infantum include Lutzomyiacruzi (Man-gabeira),Mg. migoneiPintomyia fischeri.Brazil is also home to a range of putative vectors such as Leishmania species and (iv) the presence of sandfly vectorspecies.,,CL occurs in all regions of the Brazilian Amazon. Its incidence rates are the highest inthe states of Pará (PA) and Amazonas (AM).Leishmania species: Leishmania(Leishmania) amazonensis Lainson & Shaw,Leishmania (Viannia) braziliensisVianna, Leishmania (Viannia)guyanensis Floch, Leishmania(Viannia) lainsoni Silveira, Ishikawa, Souza &Lainson, Leishmania (Viannia)lindenbergi Silveira, Ishikawa & Sousa, andLeishmania (Viannia) shawiLainson, Braga, Souza, Póvoa & Ishikawa.RO is located in the western Amazon basin; it borders the states of Acre (AC), AM and MTand it shares an international frontier with Bolivia. The state is comprised of openombrophilous forests that have been decreasing in area since the 1970s as a result ofagriculture activities. RO has the third highest incidence of CL in north Brazil, havingregistered approximately 12,000 cases between 2007 and 2018; according to the BrazilianHealth Ministry, this incidence rate is the result of intense zoonotictransmission.Bi.flaviscutellata, Ny. antunesi,Ny. umbratilis and Th.ubiquitalis,,,,,Leishmania in RO suggestthat sandflies maintain their transmission cycles in the this region.,,,Despite the presence and high diversity of known CL vectors, such as ,b (cytb), have been used as molecular markers forthe detection of their blood meal sources.-Leishmania in RO.The epidemiological knowledge of sandflies can be improved by studying their blood mealsourcesStudy areas - RO is located in the northern region of Brazil; itborders AM to the north, MT to the east and AC to the west and shares aninternational border with Bolivia to the southwest (outhwest . It has The sandfly fauna was collected in three environments: Conservation Unit (CUN) -characterised by large areas of ombrophilous rain forest; Forest Edge (FE) -characterised by small forest fragments near urban areas; and Peridomicile (PE) -areas around dwellings that are situated near small forest fragments and containenclosures where domestic animals are raised. Collections in the CUN environmentwere conducted between 2016 and 2017 at three places : the JarCollections in the FE and PE environments were conducted between 2016 and 2018 in themunicipalities of Cacaulândia and Monte Negro ; Cacoal, Ji-Paraná and Vilhena ; and Guajará-Mirim andPorto Velho .Sandfly collection and identification - In the CUN environments,collections were made along two different trails and sampling was performed twice in2016 and twice in 2017. Six Hoover Pugedo (HP) light traps were set along each trail(12 HPs/reserve) and collections were made between 06:00 p.m. and 07:00 a.m. forfive consecutive days.Collections in the FE and PE environments were made from 2016 to 2018 at fivelocations within each municipality. At each location, one trap was set in the FEenvironment and two traps were set in the PE environment, using a total of 15 trapsper municipality.Male sandflies were clarified in 10% potassium hydroxide (KOH), washed in 10% aceticacid and slide-mounted in Berlese fluid. Females were divided into engorged andnon-engorged specimens, and their heads and genitalia were clarified andslide-mounted as above. The thorax and abdomen of each female were stored in amicrotube with 96% ethylic alcohol for further molecular analysis. Speciesidentification was carried out using the morphological characters described byGalati.Molecular detection of Leishmania - Females were sorted accordingto species abundance, collection location and environment type and were separatedinto pools of 2-20 specimens. DNA extraction and polymerase chain reaction (PCR)assays were performed by targeting kDNA and hsp70, as describedelsewhere.,Th. ubiquitalis males and theLe. amazonensis reference strain IOC/L0575(IFLA/BR/1967/PH8) were used as positive controls and ultrapure water was used asthe negative control.Sandfly blood meal sources - Engorged females were separatedaccording to species, municipality, and environment type. During DNA extraction,three samples were used as negative controls: one sample containing DNA-free waterand two samples containing a female sandfly with no blood present in the gut. DNAextraction was carried out using the phenol/chloroform protocol described bySambrook and Russell.cytb 1 andcytb 2, which are complementary to the conserved region of thecytb gene in vertebrate mitochondrial DNA.®, Madison, WI, USA), 1.5 µL of each primer and 5 µL ofDNA (< 250 ng). The amplifications were performed in a thermocycler with an initialdenaturation of 95ºC for 5 min, followed by 35 cycles of denaturation at 95ºC for 30s, annealing at 53ºC for 30 s and extension at 72ºC for 1 min, with a finalextension at 72ºC for 6 min. Amplified products were purified using the QIAquickPurification Kit  and submitted to the Fiocruz SequencingFacility .The PCR amplification was carried out in a 50 µL reaction volume containing 25 µL(1X) Go Taq Colorless  wereused to evaluate sample coverage and compare diversity indexes (Shannon and Simpson)between environments. Comparisons were made using Hill numbers expressed as order qvalues, and the data were analysed in the R program.cytb) were analysed using the Phred, Phrapand Consed software programs,The sequences , Ny. antunesi ,Th. auraensis  and Th.ubiquitalis ; these four species comprised 57% of allindividuals collected.A total of 73 species and 14 genera were identified from 9,535 individuals . Owing tA sample coverage analysis indicated that sandfly populations were sufficientlyrepresented in all environments. The CUN, FE and PE environments yielded 5,847,2,111 and 1,457 individuals and 68, 58 and 47 species, respectively, at 99% samplecoverage .Species diversity was the highest in the CUN environments, followed by the FE and PEenvironments. The CUN environments yielded the highest Shannon index (H’) = 19.5common species and Simpson index (1/D) = 6.9 dominant species, followed by FE withH’ = 14.5 common species and 1/D = 6.9 dominant species and PE with H’ = 10.3 commonspecies and 1/D = 5.2 dominant species , Fig. 2.kDNA and hsp70 identified one pool ofPs. davisi infected with Le.(Vi.) braziliensis   . The infBi.flaviscutellata (1), Ny.antunesi (4), Psathyromyia dendrophyla (2),Ps. carrerai carrerai (1), Ps.davisi (6) and Ps. hirsutushirsutus (1). The samples were used to amplify a 358 bp fragment of thecytb gene. The resultant sequences were compared with theGenBank sequences, leading to the identification of three vertebrates with 98-100%similarity: Bos taurus, Homo sapiens andTamandua tetradactyla .Ny. antunesi, Ps. davisi andTh. ubiquitalis were abundant in all environments. Humansgenerally come in close proximity to forest fragments while engaged in agricultureor activities like hunting and fishing. These activities increase the risk ofexposure to Leishmania vectors in possible transmission foci,,) and that risk is exacerbated by the abundance of Ny.antunesi, Ps. davisi and Th.ubiquitalis in the areas we studied. One pool of Ps.davisi tested positive for Le.(Vi.) braziliensis DNA in the municipality ofMonte Negro. This finding is significant because Le.braziliensis is responsible for 50% of human CL cases in therural population of Monte Negro.,Ps. davisi is an abundant species in this region,,,Ps. davisi individuals have beenpreviously found to be infected with Le. (Vi.)braziliensisLe. (Vi.) naiffi.Ps. davisi might act as a vector inRO.The sandfly species Ny. antunesi and Th.ubiquitalis might act as vectors in RO. Both species were foundin high abundance in this as well as other studies conducted throughout thestate,,,,Leishmania has been demonstrated in the two studies performedin Porto Velho.,,Furthermore, Ny.whitmani, Ps. carreraicarrerai, Ps. complexus,Ps. hirsutus hirsutus and Th.auraensis. Ny. whitmani has already beenrecorded in abundance in RO.,Ny. whitmani and Ps.hirsutus hirsutus were found in high abundance in the FEenvironments, suggesting that these species are confined to degraded environments;both species have been associated with dense forest environments,,Leishmania inRO;,,,Leishmania in PA.Other abundant species found in RO included , Ps. carrerai carrerai occurs mainly in denseforest environments.,,Ps. carrerai carrerai andPs. complexus in this region.,Ps. carrerai carrerai has been found to carry promastigoteflagellates identified as Le. (Vi.)braziliensisLeishmania DNA.In ROTrichophoromyia auraensis is abundant primarily in themunicipalities of Guajará-Mirim and Porto Velho and in central RO,Leishmania DNA has been detected in females.,Th. auraensis was found abundant only in theCUN environments; however, the natural infection of Th.auraensis by Leishmania spp has beenreportedTh. auraensis has been found inabundance in both FE and PE environments in AC of western Brazil.,cytb gene led tothe identification of the DNA belonging to humans (H. sapiens),domestic animals (Bos taurus) and sylvatic animals such asanteaters (T. tetradactyla). The DNA belonging to Bostaurus and H. sapiens was present in samples fromevery collection made in the PE and FE environments, and this DNA was found in theblood taken from 13 female specimens belonging to the species: Bi.flaviscutellata, Ny. antunesi,Pa. dendrophyla, Ps.carrerai carrerai, Ps. davisiand Ps. hirsutus hirsutus. The T.tetradactyla DNA was present in the blood sample taken from twoNy. antunesi females captured in the FEenvironments. Although 15 engorged females represents a small sample size relativeto other studies, our findings are significant because previous studies targetingthe cytb gene have detected the DNA of only domestic animals, suchas cats, dogs, chickens, bovines, equines and pigs.-In our analysis of blood meal sources, blood was taken from the stomachs of 15engorged females, and the PCR amplification of the Tamandua spp) act as possible reservoirs forsome Leishmania species, such as Le.(Vi.) guyanensis,,,,Bos taurus, might have attracted sandflies from the forestfragments.Preserved environments showed the highest variety of blood meal sources forsandflies, and a large variety of blood meal sources guarantees the maintenance ofthe gonotrophic cycle.Ps.davisi was subjected to PCR targeting the cytbgene; this led to the identification of Gallus gallus as a bloodmeal source.Ny. antunesiand Ps. davisi, feed on humans and bovines in thePE environments and feed on sylvatic animals, such as anteaters in the FEenvironments.Few studies have examined the importance of blood meal sources in the BrazilianAmazon. Recently, in the municipality of Rio Branco (AC), the blood collected fromthe intestinal contents of the two specimens of Our study largely corroborates the findings of previous studies concerned with thetransmission cycle of leishmaniasis in RO. However, the fact that sandflies areusing humans and domestic animals as blood meal sources indicates that thetransmission profile might be changing in the PE environments. These findings can beused to enhance the epidemiological surveillance of leishmaniasis in RO.


C. jejuni and C. coli prevalence, and investigate their susceptibility to antimicrobials. Risk of shedding C. jejuni was higher in cattle than sheep , whereas risk of shedding C. coli was higher in sheep than in cattle . Susceptibility to six antimicrobials was determined by broth microdilution using European Committee for Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off values. C. coli exhibited higher resistance  than C. jejuni , and resistance was more widespread in isolates from dairy cattle than beef cattle or sheep. Compared to results obtained 10-years earlier (2003–2005) in a similar survey, an increase in fluoroquinolone-resistance was observed in C. jejuni from beef cattle , and a decrease in tetracycline-resistance in C. jejuni from dairy cattle . Resistance to macrolides remained stable at low rates and restricted to C. coli from dairy cattle, with all macrolide-resistant C. coli showing a pattern of pan-resistance. Presence of the single nucleotide polymorphisms (SNPs) associated to quinolone and macrolide resistance was confirmed in all phenotypically resistant isolates. The increase in fluoroquinolone resistance is worrisome but susceptibility to macrolides is reassuring.A cross-sectional survey was conducted in 2014–2016 in 301 ruminant herds to estimate  Campylobacter is the main cause of food-borne gastroenteritis in industrialized countries and the cause of the most frequently reported zoonosis in the European Union (EU). In 2017, 246,158 confirmed cases of campylobacteriosis in humans were reported in the EU, which accounted to an average notification rate of 64.8 per 100,000 population [Campylobacter infection causes underreporting and hampers the identification of the infection source [Campylobacter is also highly prevalent in ruminants worldwide, and there is increasing evidence that the contribution of ruminant Campylobacter to campylobacteriosis in humans is also considerable, with cattle being the second most important reservoir after broilers for C. jejuni human infection and sheep the first for C. coli infections in humans [Campylobacter from ruminant feces can contaminate water supplies and fresh products via agricultural run-off water [Campylobacter infections or in immunocompromised patients. However, the emergence of Campylobacter strains resistant to the antimicrobial agents of choice (macrolides for laboratory-confirmed cases and fluoroquinolones for cases of diarrhea) compromises the therapeutic efficacy [n source . Althougefficacy ,10. Campylobacter in human campylobacteriosis [Campylobacter prevalence in ruminants  and investigate their susceptibility to antimicrobials is small compared to the large number of studies carried out in poultry. In a previous study (2003–2006) carried out in ruminants in the Basque Country (Northern Spain), 62.1% of cattle herds and 55.0% of sheep flocks were Campylobacter-positive, identifying C. jejuni and C. coli in 21.8% and 5.9% of the farms, respectively [Campylobacter species were targeted and only one isolate per positive farm was identified, so that species like C. hyointestinalis in cattle or C. lanienae in sheep contributed to the high prevalence of the genus Campylobacter [C. jejuni isolates were then characterized for antimicrobial resistance showing high levels of resistance to tetracyclines and quinolones [C. jejuni and C. coli in ruminant herds in the Basque Country; (ii) to determine the antimicrobial resistance (AMR) profiles of C. jejuni and C. coli; (iii) to compare antimicrobial resistance in Campylobacter isolated from ruminants in two studies carried out 10-years apart; and, (iv) to investigate the potential of a highly discriminatory and rapid method for estimating the true prevalence of Campylobacter macrolide-resistance under an apparently low prevalence situation.Despite the role of ruminant teriosis ,11,12, tectively . In thatlobacter . A few Cinolones . Now, 10C. jejuni and/or C. coli was 78.8% (82/104) of beef cattle, 86.6% (71/82) of dairy cattle and 54.8% (63/115) of sheep flocks, the difference in proportions being statistically significant between cattle and sheep (p < 0.001)  of the tested herds/flocks both C. jejuni and C. coli were detected. Univariate analysis did not identify any significant explanatory variables associated to Campylobacter shedding. Multivariate analysis using host species (cattle vs. sheep) as principal explanatory variable for C. jejuni herd prevalence showed that cattle presented significantly higher risk of shedding C. jejuni than sheep (ORadj = 5.22 (3.11–8.89), p < 0.001), and also when considering the farm system as the principal variable and comparing beef cattle and dairy cattle with sheep separately (dairy cattle vs. sheep: ORadj = 7.07 (3.46–14.43), p < 0.001; beef cattle vs. sheep: ORadj = 4.27 (2.36–7.70), p < 0.001). No associations were found between C. jejuni or C. coli shedding and any of the other variables tested. Risk of shedding C. coli was non-significantly higher in sheep than in cattle (ORadj = 1.71 (0.86–3.40), p = 0.128). However, no differences were found between dairy and beef cattle.The proportion of herds positive to < 0.001) . C. jejuC. jejuni isolates and 34 C. coli isolates; distributions of minimum inhibitory concentrations (MICs) are shown in C. coli than C. jejuni isolates (C. jejuni and 94.1% (32/34) of C. coli isolates showed resistance to at least one of the six antimicrobial agents tested. C. coli exhibited higher resistance to tetracycline (76.5%), streptomycin (67.6%) and quinolones (64.7%), whereas in C. jejuni resistance to quinolones (60.6%) was the most common followed by resistance to tetracycline (38.5%)  but very high for streptomycin (67.7%). Finally, resistance to erythromycin (macrolide) was low (8.8%) and only detected in C. coli isolated from dairy cattle herds. No relationship was found between host species or farm system and resistance against each of the antimicrobial agents tested in neither C. jejuni nor C. coli isolates. However, MIC values for C. jejuni susceptible to gentamicin and streptomycin were higher in sheep than in cattle isolates , whereas MICs for C. coli resistant to ciprofloxacin and tetracycline were higher in cattle than in sheep isolates . Sensitivities to six antimicrobials (four classes) were determined by broth microdilution for 109 isolates  and the isolates . Overall (38.5%) . ResistaCampylobacter species, but only C. coli isolates presented different profiles according to host , defined as resistance to three or more classes of antimicrobial agents, was present in significantly higher proportions (odds ratio (OR) = 20.72, p < 0.001) in C. coli  than in C. jejuni  isolates and, albeit at different levels, this trend was observed in each host , and considerably higher in dairy cattle (OR = 72.00) , p = 0.053). The most common MDR pattern was to CIP-NAL-STR-TET  at similar levels as sheep (14.0%), whereas beef cattle had the lowest (10.6%)  . Among C-STR-TET . All thr (10.6%) . gyrA gene of quinolone-resistant C. coli. The results obtained with the real-time PCR SNP discrimination assays were in fully agreement with the phenotypic antimicrobial sensitivity test results. Thus, all C. jejuni (66) and C. coli (24) isolates that were phenotypically resistant to ciprofloxacin and nalidixic acid contained the C257T mutation in the gyrA gene. However, one C. coli isolate from a sheep farm failed to give any hybridization results when analyzed with the C. coli-specific gyrA SNP detection real-time PCR, but provided a resistant profile when using the C. jejuni-specific gyrA SNP assay. Sequencing analysis of the gyrA gene demonstrated that this isolate had a typical C. jejuni gyrA allele. The SNP mutation associated to resistance to macrolides (A2075G in the 23S rRNA genes) was found in the only three C. coli isolates that were phenotypically resistant to erythromycin. In all three isolates, MIC values were far above the highest concentration tested (>128 mg/L) and therefore far higher than the MIC epidemiological cut-off value. Sequencing analysis demonstrated the analytical specificity of the newly developed TaqMan assay to detect the point mutation C257T in the Campylobacter was only isolated from one dairy cattle herd when directly picking colonies from the CASA® plate without selective isolation. When DNA extracted from CASA® cultures that tested C. jejuni and/or C. coli-positive were screened by real-time PCR for the macrolide-resistance associated SNP, another three dairy cattle herds tested positive, and in two of them erythromycin-resistant C. coli strains were confirmed after selective isolation in erythromycin-containing media; in the third herd no isolates could be recovered. Hence, prevalence of dairy cattle shedding macrolide-resistant Campylobacter was 3.7% (3/82) of herds. Macrolide-resistant C. jejuni isolates from beef cattle , p = 0.020). However, resistance to tetracyclines in C. jejuni from dairy cattle decreased from 75.0% to 43.2% (OR = 0.25 (0.08 – 0.85), p = 0.026). In C. coli, no significant changes were observed in the proportion of isolates resistant to each antimicrobial, but MIC values among isolates susceptible to erythromycin were significantly lower in the present study (p < 0.001), particularly in isolates from beef cattle (p = 0.034).Comparison of results from this study (2014–2016) and those from the study carried out 10 years earlier (2003–2005) showed a significant increase in the proportion of fluoroquinolone resistance in C. coli isolates resulted in 13 ST-types, 12 of them belonging to clonal complex (CC)-828 and another (ST-8857) not assigned to any recognized CC, and described in this study for the first time. The most common ST type (ST-827) accounted for 38.2% of the C. coli isolates typed, and was the most prevalent type in sheep  but not in cattle . All macrolide resistant isolates belonged to ST-2097, a ST-type associated to the three macrolide-resistant C. coli isolates plus another MDR C. coli (CIP-NAL-GEN-STR-TET) isolated also from dairy cattle.MLST analysis of 34 C. jejuni and C. coli herd prevalence in dairy cattle, beef cattle and sheep in the Basque Country, along with a collection of representative strains and their corresponding antimicrobial resistance profiles. Results showed a widespread distribution of both zoonotic Campylobacter species in ruminants, prevalence being higher than that reported in a study carried out in the same region in 2003–2005 [Campylobacter herd level prevalence has been reported in other studies [C. jejuni than sheep, while risk of shedding C. coli was non-significantly higher in sheep than in cattle. This situation might reflect differences in the epidemiology of C. jejuni and C. coli. In this sense, increasing evidence suggests that sources and epidemiology of C. coli and C. jejuni infections are different. Thus, whereas sheep are associated to only 2.5%–24% of C. jejuni human infections [C. coli clinical cases were attributed to sheep, a proportion similar to that assigned to chicken (40%) and lower than that attributed to cattle (14%) [C. coli in sheep flocks as described here might explain the significant contribution of sheep to human infection with C. coli. On the other hand, it has been suggested that strains isolated from sheep belonged to genotypes that commonly cause disease in humans. Here, half of the strains from sheep belonged to ST-827, one of the genotypes most frequently found in humans [C. coli STs of ruminant origin compared to C. jejuni [C. coli from swine or poultry [C. coli isolate from a sheep farm (ST-5380) showed a typical C. jejuni gyrA sequence suggestive of genome introgressed from C. jejuni as previously described for other C. coli strains belonging to CC-828 [This cross-sectional study provided estimates of 003–2005 , an appa studies ,17,18. A studies , we founfections ,12, 41% o CC-828 . C. coli than in C. jejuni in all three host species, as was MDR. An overall higher resistance in C. coli than C. jejuni has already been reported in different hosts and for different antibiotics [C. jejuni isolates resistant to fluoroquinolones in beef cattle between the two studies carried out 10-years apart but a decrease in resistance to tetracyclines in dairy cattle. In fact, resistance to tetracycline was much lower than that reported for C. jejuni isolated from calves in Spain (83.3%) within the EU survey on AMR in zoonotic and indicator bacteria in 2017 [ca. 32% of total sales) in the EU and Spain [Campylobacter from food-producing animals [Campylobacter to fluoroquinolones has been reported worldwide [C. jejuni and C. coli observed in the present study were higher than those found in ruminants in other EU countries [gyrA mutation associated to fluoroquinolone resistance has been described to impose certain fitness burden on Campylobacter [Campylobacter is prevalent it can persist for years even in the absence of antibiotic selection pressure so that a reversal in resistance trend might be difficult to achieve [C. coli isolated from dairy cattle and at similar levels to those reported elsewhere [erm(B) gene [C. jejuni isolates, lower than that reported in the EU for cattle isolates [C. coli resistance to aminoglycosides was higher, reaching similar levels to those reported in isolates from pigs [C. jejuni, but all C. coli isolates resistant to erythromycin were also resistant to fluoroquinolones.Regarding AMR, differences in methodology and results interpretation hamper comparisons among studies available in the bibliography. Here, EU harmonized methods were used, MICs were determined by broth microdilution, and European Committee for Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off values were used to determine microbiological resistance . In thisibiotics ,24,25,26nd Spain . This wo animals . The higorldwide ,29, but ountries ,31,32, tountries . Use of ountries . In a suountries . Althouglobacter , once fllsewhere ,24,25 an(B) gene . ResistaC. coli in two herds that had tested negative when using non-selective isolation. Results demonstrated the usefulness of the method in providing more reliable estimates of macrolide-resistance than procedures that analyze a single colony per sample and likely underestimate the real prevalence. Under a low prevalence situation, PCR screening followed by selective isolation provides the processability needed to carry out extensive antimicrobial surveillance. Here it was only applied to macrolides, but a similar approach could also be used to screen for C. jejuni and C. coli quinolone resistance prevalence in regions where expected resistance levels were not as high as those found here. Finally, the PCR-based screening method followed by selective isolation in erythromycin-containing media developed here allowed the isolation of macrolide-resistant C. jejuni and C. coli in cattle herds and sheep flocks in the Basque Country (Northern Spain). Cattle included both dairy and beef herds, and sheep were of the Latxa dairy breed. Details on general husbandry systems for beef cattle, dairy cattle and sheep in the region were reported elsewhere [A cross-sectional survey was carried out to estimate the prevalence of lsewhere . BrieflySampling was carried out throughout the year, and a total of 301 herds  were visited once between February 2014 and June 2016. Rectal fecal samples from 25 animals randomly selected per herd were collected with a gloved hand, and a 25 g-pool was prepared  for microbiological analyses. Sample collection was carried out by veterinary clinicians as part of the usual health monitoring procedures performed on farms, strictly following Spanish ethical guidelines and animal welfare regulations . The collection of this material, being considered as routine veterinary practice, did not require the approval of the Ethics Committee for Animal Experimentation. Informed oral consent was obtained from the farm owners at the time of sample collection.Campylobacter spp., 25 g of pooled rectal fecal samples were diluted 1/10 in Preston broth, homogenized and incubated for 18±2 h at 42 ℃ for enrichment. Suspensions (0.1 mL) were then subcultured onto a Chromogenic-Campylobacter Selective Agar  and incubated at 42 ℃ in a microaerobic atmosphere  for 48–72 h. To confirm the presumptive Campylobacter and identify the species present in the pool of feces, DNA was extracted from a loopful of bacterial culture  and screened for the presence of C. jejuni and C. coli in a multiplex real-time PCR . Individual colonies were then tested using the same multiplex real-time PCR to confirm their identity and were stored for further characterization. For the isolation of thermophilic ® MIC Susceptibility Plate  containing two-fold serial dilutions of six antimicrobial agents  following recommendations by the Commission Decision 2013/652/EU. MIC results were interpreted using epidemiological cut-off values (ECOFF) as developed by the European Committee for Antimicrobial Susceptibility Testing  to define microbiological resistance.Minimum inhibitory concentrations (MIC) were determined by broth microdilution using SensititregyrA gene, Thr-86-Ile) resistance. Primers and probes used for C. jejuni (macrolide and quinolone) and C. coli (macrolide) were as described before [gyrA gene) in C. coli, new primers and probes targeting a 101 bp fragment of the gyrA gene of C. coli were designed in this study  and quinolone , a PCR-based screening method followed by selective isolation in media containing erythromycin was assessed. Thus, DNA was extracted from a loopful of bacterial culture grown in CASA® agar . All samples that tested PCR-positive were then selectively isolated in Preston broth supplemented with erythromycin , and individual colonies (presumptive macrolide-resistant colonies) were identified to the species level by real-time PCR and MICs were determined as above.In order to increase chances of isolation of macrolide-resistant agar see  from allC. jejuni isolates from a similar study carried out in the region in 2003–2005 . As part of this study, MIC values and presence of point mutation associated to quinolone and macrolide resistance were determined for a further 32 C. jejuni and 17 C. coli isolates from that previous study. Statistical analyses of the results from both studies were performed as described below  and subjected to multilocus sequence typing (MLST) of seven housekeeping genes  as previously described [Campylobacter MLST database PubMLST (http://pubmlst.org/campylobacter/), developed by Keith Jolley and Man-Suen Chan and sited at the University of Oxford, for type (ST) and clonal complex (CC) assignation. Novel STs were submitted to the Campylobacter MLST database for assignation of new numbers.escribed ,40. The Campylobacter, C. jejuni, C. coli) were categorized as follows: Host species ; farm system ; sampling season , geographical location of the farm ; and presence of other species in the farm such us cattle, sheep, goats, horses . First, univariate logistic regressions were conducted to explore the unadjusted association between herd positivity and variables. Only significant factors  were included for further multivariate logistic regression analysis. Test of overall significance (chunk test) was performed to assess any possible effect modifiers that could bias the magnitude of associations, and interactions with a value of p > 0.05 were excluded until no significant difference between the full and the reduced models was observed. To identify confounding variables, the measure of association was estimated before and after adjusting for the potential confounder, and variables causing change of ≥ 10% in the estimated measure were retained. Adjusted odds ratios (ORadj) were used as the measure of association between positivity and the explanatory variable, and were expressed with their confidence interval at 95% (95% CI).Herd-level prevalences were expressed as the percentage of herds/flocks that tested positive in each farm system out of all herds/flocks that were examined in the respective farm system, with 95% confidence intervals adjusted for the population size, using the software EpiInfo2. Variables selected to check for statistical differences in shedding prevalence of each pathogen  and those from the study carried out 10 years earlier (2003–2005) were also compared. Qualitative assessment (resistant or susceptible outcome) was done with logistic regression and quantitative comparisons  with linear regression. In all cases, regression analyses were performed separately for C. jejuni and C. coli and for each specific antimicrobial agent. All analyses were conducted in Stata/IC version 13.1 statistical software (StataCorp LP) and figures were elaborated with Microsoft Excel and with ggplot2 package of R statistical software (v.3.3.2).Simple logistic regression tests were performed to determine associations between resistance against the antimicrobial agents tested and host species (sheep vs. cattle) or farm system . The same approach was also used to investigate whether resistance against each antimicrobial agent was more likely to be present on either C. jejuni and C. coli in ruminants, with cattle as the main reservoir of C. jejuni and sheep of C. coli, thus highlighting the importance of non-poultry reservoirs for Campylobacter infection. AMR was significantly more prevalent among C. coli than C. jejuni isolates, and higher in isolates from dairy cattle than beef cattle or sheep. An increase in fluoroquinolone resistance was observed, highlighting the need to promote prudent use of these antimicrobials. Resistance to macrolides, the antibiotic of choice for the treatment of Campylobacter-associated diarrhea , remained stable at low rates and restricted to C. coli, which was reassuring. Still, antimicrobial surveillance in campylobacters from livestock is needed for early detection of emerging resistance, and the PCR-based screening method developed here proved to be a valuable tool to achieve the processability required for the analysis of a relatively large number of samples. This study showed a widespread distribution of


Aflatoxin is considered a “hidden poison” due to its slow and adverse effect on various biological pathways in humans, particularly among children, in whom it leads to delayed development, stunted growth, liver damage, and liver cancer. Unfortunately, the unpredictable behavior of the fungus as well as climatic conditions pose serious challenges in precise phenotyping, genetic prediction and genetic improvement, leaving the complete onus of preventing aflatoxin contamination in crops on post-harvest management. Equipping popular crop varieties with genetic resistance to aflatoxin is key to effective lowering of infection in farmer’s fields. A combination of genetic resistance for in vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC) and aflatoxin production together with pre- and post-harvest management may provide a sustainable solution to aflatoxin contamination. In this context, modern “omics” approaches, including next-generation genomics technologies, can provide improved and decisive information and genetic solutions. Preventing contamination will not only drastically boost the consumption and trade of the crops and products across nations/regions, but more importantly, stave off deleterious health problems among consumers across the globe. Aspergillus species such as Aspergillus flavus, Aspergillus parasiticus, Aspergillus nomius and Aspergillus tamarii [A. flavus while G1 and G2 are produced by A. parasiticus. In addition to health issues, aflatoxin levels beyond a threshold hamper the export quality of groundnuts 20 parts per billion (ppb) in the USA and 4 ppb in Europe [Aflatoxin contamination is a food safety concern that has adverse financial implications and health consequences in groundnut growing regions across the globe. Aflatoxins are a group of mycotoxins and highly toxic secondary metabolites produced by four  tamarii ,2,3. Gro tamarii . Aflatox tamarii ,6. Amongn Europe  resultinn Europe . Althougn Europe ,10,11, tAspergillus infection in the field. Speedy advancements in low-cost sequencing technologies and big data analysis provide opportunities to dissect this tricky trait by deploying complex multi-parent genetic populations  [Inconsistent phenotyping results from aflatoxin contamination experiments suggest a large variation in germplasm due to genotype-by-environment (G×E), but studies have not led to the identification of stable resistance sources among diverse germplasm. Studies have reported the existence of three types of host-pathogen resistance mechanisms, namely in vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC) and aflatoxin production (AP) detected in different genetic backgrounds ,14,15,16mapping) ,18,19. FArachis duranensis [A. ipaensis [A. monticola [A. hypogaea spp. hypogaea [A. hypogaea spp. fastigiata [Arachis’ Array [aflR, aflS, aflep and aflC) using RNAi approach [aflM and aflP genes through host-induced gene silencing (HIGS) and overexpressing of antifungal plant defensins MsDef1 and MtDef4.2 [Over the last decade, next-generation sequencing (NGS) technologies accelerated the development of different genomic resources in a given crop that are very affordable even for large genome-polyploid crops such as groundnut ,19. As aranensis ,21 and Aipaensis  wild tetonticola  and alsohypogaea  and A. hstigiata ,26 of custigiata ,28, largs’ Array  for use s’ Array ,31,32. Tapproach . TransgeMtDef4.2 .Since none of the above-mentioned efforts have provided heritable resistance in the genetic background of popular cultivars, serious efforts are warranted in achieving stable genetic resistance. However, it must be mentioned that post-harvest management practices have been very instrumental in mitigating contamination in the entire food chain. This paper discusses the importance and strategy of combining different resistance mechanisms together with well-tested pre- and post-harvest management and safety practices to deliver aflatoxin-free groundnuts to the food chain . It alsoA. flavus which is a soil saprophytic fungus and opportunistic pathogen that impacts human and animal health. A. flavus grow well at 28–30 °C and 25–35 °C and is readily able to colonize in most environments whenever there is a suitable nutrient rich source of carbon and nitrogen [A. flavus mode of replication is majorly by asexual reproduction, but it also forms sclerotia or conidia in soil and in plant tissue as hardened masses of desiccated and melanized mycelia that are able to survive adverse nutritional conditions [A. flavus strains [A. flavus are powdery masses of yellow-green spores and reddish gold on the upper and lower surface area. Most of the plants which were invaded and/or colonized by A. flavus do not show any visible symptoms on the foliage except aflatoxin accumulation in the grains/seeds.Polyketide derived aflatoxins are produced by nditions . However strains . FurtherA. flavus leading to infection in groundnut seeds [A. flavus and A. parasiticus [1, AFB2, AFG1 and AFG2 based on fluorescence emission and their relative mobility on silica gel. Of these, AFB1 is most toxic and is produced by both A. flavus and A. parasiticus. AFG1 and AFG2 are produced exclusively by A. parasiticus. Infections from A. flavus are more prevalent in Asia and Africa while A. parasiticus is prevalent in Americas. Groundnuts tend to be colonized and contaminated by Aspergillus sp. at different stages and aflatoxin production occurs at pre-harvest, during harvest, post-harvest drying, in storage and also during transportation along the value chain [Groundnut pods develop beneath the soil, which is the main source of inoculum for ut seeds ,39. The ut seeds . Based out seeds  Aflatoxiasiticus . Aflatoxue chain ,44.A. flavus [Aflatoxin contamination in groundnuts is aggravated by heat and drought stresses ,46. Unde. flavus . Damaged. flavus . Under d. flavus . Thus, d. flavus . Althoug. flavus . It has . flavus  and afla. flavus  and oxyg. flavus ,55,56,57A. parasiticus and A. flavus [α (FAS α), FAS β and the polyketide synthase (PKS). The average size of the other 22 genes is about 2 Kb towards 5’ end with no ORF. The expression of the two transcriptional regulators (aflR and aflS) are controlled by many regulators, i.e., CreA transcription factor, VelB/VeA/LaeA complex, and a cell surface-localized G-protein coupled receptor complex [1 production in crops with a few dwelling on factors responsible for aflatoxin contamination.The aflatoxin biosynthetic pathway has been well characterized in . flavus . Extensi. flavus ,60,61,62 complex ,63. Most1) has also been categorized as a class 1 carcinogen by the International Agency for Research on Cancer (IARC). This has resulted in the regulation of toxins to very low concentrations, i.e., 20 ppb in grains and 0.5 ppb in milk in the United States and 4 ppb in food for direct consumption (including groundnut) in some European countries [Aflatoxin adversely affects >5 billion people who are chronically exposed to a large amount (>1000 ppb) of toxin . The expountries .http://scienceinafrica.com/health/aflatoxin-peanut-butter-mrc-policy-brief).In addition to groundnuts, aflatoxin also contaminates linseeds, sunflower seeds, cereals, beans and poultry due to contaminated feed . ReportsAspergillus species, growing and storage conditions and differ from country to country [Levels of aflatoxin contamination depend on the  country ,82. Fact country . A study country .Standard food safety parameters set by national regulatory bodies in different countries for the benefit of human health and permissible limits differ among countries . This maA. flavus infection and aflatoxin production (1) and aflatoxin B2 (AFB2) content. Two QTLs for PSII and 12 QTLs for aflatoxin accumulation were detected by unconditional analysis. Interestingly, four QTLs (qAFB1A07 and qAFB1B06.1 for AFB1 and qAFB2A07 and qAFB2B06 for AFB2) showed major and stable effects (9.32%–21.02% PVE) [qAFB1A07 and qAFB2A07) and on A06 (qAFB1B06.1 and qAFB2B06). A closer look at the genotyping and phenotyping data suggested additive effects between two QTLs (qAFB1A07 and qAFB1B06.1) leading to low AFB1 and AFB2 accumulation [Deciphering genotype to phenotype association requires an understanding of gene networks and pathways of biological systems to target complex traits such as aflatoxin contamination in groundnut. Multiple efforts have been made for phenotyping diverse groundnut genotypes leading to identification of several promising lines showing resistance/moderate resistance for oduction . Modern oduction . A very 02% PVE) . It was mulation . These aA. flavus seed colonization [Aspergillus infection [Aspergillus spp. [Aspergillus sp. [Genome sequencing of hosts and pathogens have provided insights into complex genetic architecture and novel genes. Further, transcriptomic and proteomic studies have supplemented information on gene expression and the pathways enrichment that govern phenotype. Previously, efforts were made in large-scale sequencing of cDNA to discover the gene expression pattern between susceptible and resistant genotypes and identified defense-related genes upon nization ,98,99. Hnization ,101,102.nfection ,31,32. SA. flavus [2O2 and their global proteome variations were studied. As a result, 1173 proteins were identified, and among them 220 were differentially expressed, controlling toxigenic abilities of strains AF13, NRRL3357 and K54A. This suggests that the toxin production abilities of toxigenic strains involve a group of genes that together regulate production of lytic enzymes, oxidative stress tolerance, production of secondary metabolites, pathogenicity, mycelial development, carbohydrate metabolism, etc. [Proteomic studies have greatly enhanced the understanding of gene regulation and regulatory networks to explain the molecular mechanism involved in host-pathogen interaction and aflatoxin contamination ,104,105 . flavus . Though . flavus . Recentlsm, etc. ,106. Togsm, etc.  and grousm, etc.  through A. flavus translates 12,000 functional genes and comprises duplication of some lineage-specific genes which give rise to the larger genome i.e., 37 Mb [A. flavus is anticipated to contain ~56 secondary metabolite gene clusters [The genome of ., 37 Mb . The comclusters ,112. Amoclusters . Furtherclusters .A. flavus, the production of secondary metabolites is a highly coordinated molecular process involving a dynamic network of transcription factors that orchestrate the coordinated expression of the target biosynthetic genes of the pathogen and suppression of the host immune responses. The aflatoxin biosynthesis pathway-specific regulatory gene aflR encodes a DNA-binding zinc-cluster protein that binds to the promoter region of the aflatoxin pathway genes to trigger their expression [aflR increases the transcript abundance of aflatoxin pathway genes [aflS, located divergently next to aflR, separated by a small intergenic region and having an independent promoter. Unlike AflR, the role of AflS is still not well defined because the deletion of aflS does not influence expression of aflatoxin biosynthetic genes. However, surprisingly, the deletion of gene aflS can abolish aflatoxin production in A. flavus [AflS can plausibly play a crucial role in aflatoxin biosynthesis through transcriptional regulation of expression of AflR [AflR and AflS in A. parasiticus [AflS is essential for appropriate transportation of AflR to or from the nucleus and that it assists in AflR localization [A. flavus. The knock-out of DmtA (a putative cytosine methyltransferase) in A. flavus could result in reduced conidiation and sclerotial production, and attenuate strain virulence due to suppression of aflC, aflK, aflO, aflS and aflR [spds), has been characterized as a key gene required by Aspergillus toxigenic strain controlling fungus seed colonization, aflatoxin production and pathogenesis [In pression . Therefoay genes . Aflatox. flavus . Therefo of AflR , becauseasiticus . More relization . Furtherand aflR . Recentlogenesis .Aspergillus spp. involves the production of resveratrol  by developing seed. Resistant varieties with increased production of resveratrol upon infection exhibit enhanced resistance to in vitro seed colonization [Aspergillus infection. This is achieved by the expression of a wide range of genes involved in ROS detoxification, such as resveratrol synthase, phenylalanine ammonia lyase, chalcone synthase, catalases, superoxide dismutase, glutathione-S-transferase, senescence-associated protein, etc, [Aspergillus growth and aflatoxin production [WRKY, ERF and NAC are important transcriptional regulators of antioxidant- and pathogenesis-related genes [A. flavus resistance [Despite years of research, geneticists and molecular biologists have yet to find a stable and effective genetic solution to aflatoxin contamination. To date, breeders have identified groundnut germplasm resistant to pre-harvest and post-harvest aflatoxin contamination. Groundnut resistance to nization . The hosin, etc, . Expressoduction . These roduction ,121. Fured genes ,32. Thesed genes . The gensistance . It is aA. flavus infection and aflatoxin production is one of the most complex traits influenced by several non-genetic factors such as water stress, population diversity and density of microorganisms in the soil. Nevertheless, extensive phenotyping of large scale germplasm during multiple seasons has identified several lines with minimum infection and aflatoxin production  can be developed to perform early generation selection to identify the best lines with resistance to Aspergillus infection and aflatoxin contamination. Limited efforts have been made so far in identifying genomic regions for PAC resistance [Developing groundnut cultivars with pre-harvest aflatoxin contamination has been one of the most challenging goals of breeding programs across the globe . Conventsistance ,124, andA. flavus growth and aflatoxin production in groundnut. For example, an hpRNA construct was successfully deployed in suppressing the expression of five genes  involved either directly or indirectly in aflatoxin biosynthesis [1 and AFB2 compared to the control. Another study achieved high level of aflatoxin resistance by overexpressing antifungal defensins genes (MsDef1 and MtDef4.2) through host-induced gene silencing (HIGS) of aflM and aflP genes from the aflatoxin biosynthetic pathway [1 levels fell from an average of 2000 ppb in controls to less than 20 ppb  in the RNAi lines as determined by highly sensitive HPLC detection methods. A strong positive correlation was observed between reduction in aflatoxin levels and aflatoxin biosynthetic gene expression using qRT-PCR. These transgenic events will be subjected to further trait verification and testing to identify the most promising events with high level of resistance to Aspergillus infection and aflatoxin contamination.Several studies have reported the use of RNAi to suppress ynthesis . The tra pathway . AflatoxAspergillus infection in groundnuts is usually influenced by the aggressiveness of the fungus, genotype susceptibility, as well as soil moisture and temperature parameters [A. flavus infection and aflatoxin contamination [A. flavus by host-plant resistance/tolerance, biological control, managing environmental factors, pre-harvest crop management and finally post-harvest crop management such as drying and storage technologies [rameters . Moisturmination ,51. Hencnologies ,127. Undnologies .A. flavus and A. parasiticus strains significantly reduce aflatoxin contamination in groundnuts and maize [Pre-harvest management includes following in situ (in field) water management techniques which enable the crop to avoid moisture stress at critical stages. Research on the efficacy of water management techniques such as tied ridges and mulching in Zambia have proved that they were effective in significantly reducing pre-harvest aflatoxin contamination in groundnuts . Other cnd maize ,133.A. flavus. Jute bags are highly porous and can easily absorb moisture, and therefore foster the rapid growth and multiplication of these aflatoxigenic molds. Alternatively, hermetic storage offers a new alternative to traditional storage of grains and pods, and is a sustainable practice. Hermetic storage works on the principle of creating airtight conditions in which oxygen levels are lowered for insect, fungal and seed respiration. In a recent study conducted at ICRISAT, Purdue Improved Crop Storage (PICS) bags that rely on the principle of hermetic storage were used to safeguard groundnuts against A. flavus infestation, and subsequently lowered aflatoxin contamination levels in storage [In the case of groundnut, post-harvest handling of pods from harvest to storage is critical in managing aflatoxin build-up. High pod/seed moisture increases post-harvest molding and aflatoxin contamination. Hence proper drying of pods after harvest to 7% moisture levels is ideal to prevent the growth of fungi, including aflatoxigenic strains . Earlier storage .A. flavus infection causes no yield loss to the producer and no immediate health impact on consumers, farmers in Asia and Africa have not shown great keenness in adopting modern pre-harvest and post-harvest management practices in the processing, packaging, transportation and storage stages. Many farmers are not even aware of the adverse health impact.The age-old problem of aflatoxin contamination has yet to find a sustainable and stable solution. Given its adverse impact on health, the west has set up very stringent criteria for import that prohibits many countries in Africa and Asia from selling their produce to these countries. It is also important to note that the population in the Asian and African countries has shown great tolerance to aflatoxin. Some studies have shown aflatoxin contamination in abundance in the entire food chain, with deleterious effects on the health of consumers. Since Given that health and commerce are equally important, it is essential to minimize aflatoxin contamination in the entire food chain. This would entail deploying more precise phenotyping and diverse genetic populations together with different “omics” approaches to identify genomic regions and candidate genes for accelerated breeding through GAB. Genetic resistance will provide the much needed defense from infection in the field and post-harvest management will ensure less aflatoxin in the produce. A combination of recent advancements in modern genetics, genomics, phenomics resources, tools and technologies along with pre-post-harvest management practices could potentially provide a stable and long term solution for this complex problem.