Low immunogenicity of common cancer hot spot mutations resulting in false immunogenic selection signals.

Cancer is driven by somatic mutations that result in a cellular fitness advantage. This selective advantage is expected to be counterbalanced by the immune system when these driver mutations simultaneously lead to the generation of neoantigens, novel peptides that are presented at the cancer cell membrane via HLA molecules from the MHC complex. The presentability of these peptides is determined by a patient's MHC genotype and it has been suggested that this results in MHC genotype-specific restrictions of the oncogenic mutational landscape. Here, we generated a set of virtual patients, each with an identical and prototypical MHC genotype, and show that the earlier reported HLA affinity differences between observed and unobserved mutations are unrelated to MHC genotype variation. We demonstrate how these differences are secondary to high frequencies of 13 hot spot driver mutations in 6 different genes. Several oncogenic mechanisms were identified that lower the peptides' HLA affinity, including phospho-mimicking substitutions in BRAF, destabilizing tyrosine mutations in TP53 and glycine-rich mutational contexts in the GTP-binding KRAS domain. In line with our earlier findings, our results emphasize that HLA affinity predictions are easily misinterpreted when studying immunogenic selection processes.

Expression divergence of expansin genes drive the heteroblasty in Ceratopteris chingii.

BACKGROUND: Sterile-fertile heteroblasty is a common phenomenon observed in ferns, where the leaf shape of a fern sporophyll, responsible for sporangium production, differs from that of a regular trophophyll. However, due to the large size and complexity of most fern genomes, the molecular mechanisms that regulate the formation of these functionally different heteroblasty have remained elusive. To shed light on these mechanisms, we generated a full-length transcriptome of Ceratopteris chingii with PacBio Iso-Seq from five tissue samples. By integrating Illumina-based sequencing short reads, we identified the genes exhibiting the most significant differential expression between sporophylls and trophophylls. RESULTS: The long reads were assembled, resulting in a total of 24,024 gene models. The differential expressed genes between heteroblasty primarily involved reproduction and cell wall composition, with a particular focus on expansin genes. Reconstructing the phylogeny of expansin genes across 19 plant species, ranging from green algae to seed plants, we identified four ortholog groups for expansins. The observed high expression of expansin genes in the young sporophylls of C. chingii emphasizes their role in the development of heteroblastic leaves. Through gene coexpression analysis, we identified highly divergent expressions of expansin genes both within and between species. CONCLUSIONS: The specific regulatory interactions and accompanying expression patterns of expansin genes are associated with variations in leaf shapes between sporophylls and trophophylls.

Evolution of isoform-level gene expression patterns across tissues during lotus species divergence.

Both gene duplication and alternative splicing (AS) drive the functional diversity of gene products in plants, yet the relative contributions of the two key mechanisms to the evolution of gene function are largely unclear. Here, we studied AS in two closely related lotus plants, Nelumbo lutea and Nelumbo nucifera, and the outgroup Arabidopsis thaliana, for both single-copy and duplicated genes. We show that most splicing events evolved rapidly between orthologs and that the origin of lineage-specific splice variants or isoforms contributed to gene functional changes during species divergence within Nelumbo. Single-copy genes contain more isoforms, have more AS events conserved across species, and show more complex tissue-dependent expression patterns than their duplicated counterparts. This suggests that expression divergence through isoforms is a mechanism to extend the expression breadth of genes with low copy numbers. As compared to isoforms of local, small-scale duplicates, isoforms of whole-genome duplicates are less conserved and display a less conserved tissue bias, pointing towards their contribution to subfunctionalization. Through comparative analysis of isoform expression networks, we identified orthologous genes of which the expression of at least some of their isoforms displays a conserved tissue bias across species, indicating a strong selection pressure for maintaining a stable expression pattern of these isoforms. Overall, our study shows that both AS and gene duplication contributed to the diversity of gene function during the evolution of lotus.

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data.

BACKGROUND: The Human Leukocyte Antigen (HLA) genes are a group of highly polymorphic genes that are located in the Major Histocompatibility Complex (MHC) region on chromosome 6. The HLA genotype affects the presentability of tumour antigens to the immune system. While knowledge of these genotypes is of utmost importance to study differences in immune responses between cancer patients, gold standard, PCR-derived genotypes are rarely available in large Next Generation Sequencing (NGS) datasets. Therefore, a variety of methods for in silico NGS-based HLA genotyping have been developed, bypassing the need to determine these genotypes with separate experiments. However, there is currently no consensus on the best performing tool. RESULTS: We evaluated 13 MHC class I and/or class II HLA callers that are currently available for free academic use and run on either Whole Exome Sequencing (WES) or RNA sequencing data. Computational resource requirements were highly variable between these tools. Three orthogonal approaches were used to evaluate the accuracy on several large publicly available datasets: a direct benchmark using PCR-derived gold standard HLA calls, a correlation analysis with population-based allele frequencies and an analysis of the concordance between the different tools. The highest MHC-I calling accuracies were found for Optitype (98.0%) and arcasHLA (99.4%) on WES and RNA sequencing data respectively, while for MHC-II HLA-HD was the most accurate tool for both data types (96.2% and 99.4% on WES and RNA data respectively). CONCLUSION: The optimal strategy for HLA genotyping from NGS data depends on the availability of either WES or RNA data, the size of the dataset and the available computational resources. If sufficient resources are available, we recommend Optitype and HLA-HD for MHC-I and MHC-II genotype calling respectively.

Antibiotic Cycling Affects Resistance Evolution Independently of Collateral Sensitivity.

Antibiotic cycling has been proposed as a promising approach to slow down resistance evolution against currently employed antibiotics. It remains unclear, however, to which extent the decreased resistance evolution is the result of collateral sensitivity, an evolutionary trade-off where resistance to one antibiotic enhances the sensitivity to the second, or due to additional effects of the evolved genetic background, in which mutations accumulated during treatment with a first antibiotic alter the emergence and spread of resistance against a second antibiotic via other mechanisms. Also, the influence of antibiotic exposure patterns on the outcome of drug cycling is unknown. Here, we systematically assessed the effects of the evolved genetic background by focusing on the first switch between two antibiotics against Salmonella Typhimurium, with cefotaxime fixed as the first and a broad variety of other drugs as the second antibiotic. By normalizing the antibiotic concentrations to eliminate the effects of collateral sensitivity, we demonstrated a clear contribution of the evolved genetic background beyond collateral sensitivity, which either enhanced or reduced the adaptive potential depending on the specific drug combination. We further demonstrated that the gradient strength with which cefotaxime was applied affected both cefotaxime resistance evolution and adaptation to second antibiotics, an effect that was associated with higher levels of clonal interference and reduced cost of resistance in populations evolved under weaker cefotaxime gradients. Overall, our work highlights that drug cycling can affect resistance evolution independently of collateral sensitivity, in a manner that is contingent on the antibiotic exposure pattern.

OMEN: network-based driver gene identification using mutual exclusivity.

MOTIVATION: Network-based driver identification methods that can exploit mutual exclusivity typically fail to detect rare drivers because of their statistical rigor. Propagation-based methods in contrast allow recovering rare driver genes, but the interplay between network topology and high-scoring nodes often results in spurious predictions. The specificity of driver gene detection can be improved by taking into account both gene-specific and gene-set properties. Combining these requires a formalism that can adjust gene-set properties depending on the exact network context within which a gene is analyzed. RESULTS: We developed OMEN: a logic programming framework based on random walk semantics. OMEN presents a number of novel concepts. In particular, its design is unique in that it presents an effective approach to combine both gene-specific driver properties and gene-set properties, and includes a novel method to avoid restrictive, a priori filtering of genes by exploiting the gene-set property of mutual exclusivity, expressed in terms of the functional impact scores of mutations, rather than in terms of simple binary mutation calls. Applying OMEN to a benchmark dataset derived from TCGA illustrates how OMEN is able to robustly identify driver genes and modules of driver genes as proxies of driver pathways. AVAILABILITY AND IMPLEMENTATION: The source code is freely available for download at www.github.com/DriesVanDaele/OMEN. The dataset is archived at https://doi.org/10.5281/zenodo.6419097 and the code at https://doi.org/10.5281/zenodo.6419764. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Competitive interactions facilitate resistance development against antimicrobials.

While the evolution of antimicrobial resistance is well studied in free-living bacteria, information on resistance development in dense and diverse biofilm communities is largely lacking. Therefore, we explored how the social interactions in a duo-species biofilm composed of the brewery isolates Pseudomonas rhodesiae and Raoultella terrigena influence the adaptation to the broad-spectrum antimicrobial sulfathiazole. Previously, we showed that the competition between these brewery isolates enhances the antimicrobial tolerance of P. rhodesiae. Here, we found that this enhanced tolerance in duo-species biofilms is associated with a strongly increased antimicrobial resistance development in P. rhodesiae. Whereas P. rhodesiae was not able to evolve resistance against sulfathiazole in monospecies conditions, it rapidly evolved resistance in the majority of the duo-species communities. Although the initial presence of R. terrigena was thus required for P. rhodesiae to acquire resistance, the resistance mechanisms did not depend on the presence of R. terrigena. Whole genome sequencing of resistant P. rhodesiae clones showed no clear mutational hot spots. This indicates that the acquired resistance phenotype depends on complex interactions between low-frequency mutations in the genetic background of the strains. We hypothesize that the increased tolerance in duo-species conditions promotes resistance by enhancing the selection of partially resistant mutants and opening up novel evolutionary trajectories that enable such genetic interactions. This hypothesis is reinforced by experimentally excluding potential effects of increased initial population size, enhanced mutation rate, and horizontal gene transfer. Altogether, our observations suggest that the community mode of life and the social interactions therein strongly affect the accessible evolutionary pathways toward antimicrobial resistance.IMPORTANCEAntimicrobial resistance is one of the most studied bacterial properties due to its enormous clinical and industrial relevance; however, most research focuses on resistance development of a single species in isolation. In the present study, we showed that resistance evolution of brewery isolates can differ greatly between single- and mixed-species conditions. Specifically, we observed that the development of antimicrobial resistance in certain species can be significantly enhanced in co-culture as compared to the single-species conditions. Overall, the current study emphasizes the need of considering the within bacterial interactions in microbial communities when evaluating antimicrobial treatments and resistance evolution.

The evolutionary significance of polyploidy.

Polyploidy, or the duplication of entire genomes, has been observed in prokaryotic and eukaryotic organisms, and in somatic and germ cells. The consequences of polyploidization are complex and variable, and they differ greatly between systems (clonal or non-clonal) and species, but the process has often been considered to be an evolutionary 'dead end'. Here, we review the accumulating evidence that correlates polyploidization with environmental change or stress, and that has led to an increased recognition of its short-term adaptive potential. In addition, we discuss how, once polyploidy has been established, the unique retention profile of duplicated genes following whole-genome duplication might explain key longer-term evolutionary transitions and a general increase in biological complexity.

Obg and Membrane Depolarization Are Part of a Microbial Bet-Hedging Strategy that Leads to Antibiotic Tolerance.

Within bacterial populations, a small fraction of persister cells is transiently capable of surviving exposure to lethal doses of antibiotics. As a bet-hedging strategy, persistence levels are determined both by stochastic induction and by environmental stimuli called responsive diversification. Little is known about the mechanisms that link the low frequency of persisters to environmental signals. Our results support a central role for the conserved GTPase Obg in determining persistence in Escherichia coli in response to nutrient starvation. Obg-mediated persistence requires the stringent response alarmone (p)ppGpp and proceeds through transcriptional control of the hokB-sokB type I toxin-antitoxin module. In individual cells, increased Obg levels induce HokB expression, which in turn results in a collapse of the membrane potential, leading to dormancy. Obg also controls persistence in Pseudomonas aeruginosa and thus constitutes a conserved regulator of antibiotic tolerance. Combined, our findings signify an important step toward unraveling shared genetic mechanisms underlying persistence.

Genome-wide expression and network analyses of mutants in key brassinosteroid signaling genes.

BACKGROUND: Brassinosteroid (BR) signaling regulates plant growth and development in concert with other signaling pathways. Although many genes have been identified that play a role in BR signaling, the biological and functional consequences of disrupting those key BR genes still require detailed investigation. RESULTS: Here we performed phenotypic and transcriptomic comparisons of A. thaliana lines carrying a loss-of-function mutation in BRI1 gene, bri1-5, that exhibits a dwarf phenotype and its three activation-tag suppressor lines that were able to partially revert the bri1-5 mutant phenotype to a WS2 phenotype, namely bri1-5/bri1-1D, bri1-5/brs1-1D, and bri1-5/bak1-1D. From the three investigated bri1-5 suppressors, bri1-5/bak1-1D was the most effective suppressor at the transcriptional level. All three bri1-5 suppressors showed altered expression of the genes in the abscisic acid (ABA signaling) pathway, indicating that ABA likely contributes to the partial recovery of the wild-type phenotype in these bri1-5 suppressors. Network analysis revealed crosstalk between BR and other phytohormone signaling pathways, suggesting that interference with one hormone signaling pathway affects other hormone signaling pathways. In addition, differential expression analysis suggested the existence of a strong negative feedback from BR signaling on BR biosynthesis and also predicted that BRS1, rather than being directly involved in signaling, might be responsible for providing an optimal environment for the interaction between BRI1 and its ligand. CONCLUSIONS: Our study provides insights into the molecular mechanisms and functions of key brassinosteroid (BR) signaling genes, especially BRS1.

Distinct Expression and Methylation Patterns for Genes with Different Fates following a Single Whole-Genome Duplication in Flowering Plants.

For most sequenced flowering plants, multiple whole-genome duplications (WGDs) are found. Duplicated genes following WGD often have different fates that can quickly disappear again, be retained for long(er) periods, or subsequently undergo small-scale duplications. However, how different expression, epigenetic regulation, and functional constraints are associated with these different gene fates following a WGD still requires further investigation due to successive WGDs in angiosperms complicating the gene trajectories. In this study, we investigate lotus (Nelumbo nucifera), an angiosperm with a single WGD during the K-pg boundary. Based on improved intraspecific-synteny identification by a chromosome-level assembly, transcriptome, and bisulfite sequencing, we explore not only the fundamental distinctions in genomic features, expression, and methylation patterns of genes with different fates after a WGD but also the factors that shape post-WGD expression divergence and expression bias between duplicates. We found that after a WGD genes that returned to single copies show the highest levels and breadth of expression, gene body methylation, and intron numbers, whereas the long-retained duplicates exhibit the highest degrees of protein-protein interactions and protein lengths and the lowest methylation in gene flanking regions. For those long-retained duplicate pairs, the degree of expression divergence correlates with their sequence divergence, degree in protein-protein interactions, and expression level, whereas their biases in expression level reflecting subgenome dominance are associated with the bias of subgenome fractionation. Overall, our study on the paleopolyploid nature of lotus highlights the impact of different functional constraints on gene fate and duplicate divergence following a single WGD in plant.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches.

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

First detection of a plasmid-encoded New-Delhi metallo-beta-lactamase-1 (NDM-1) producing Acinetobacter baumannii using whole genome sequencing, isolated in a clinical setting in Benin.

BACKGROUND: Carbapenem-resistant Acinetobacter baumannii is considered a top priority pathogen by the World Health Organization for combatting increasing antibiotic resistance and development of new drugs. Since it was originally reported in Klebsiella pneumoniae in 2009, the quick spread of the blaNDM-1 gene encoding a New-Delhi metallo-beta-lactamase-1 (NDM-1) is increasingly recognized as a serious threat. This gene is usually carried by large plasmids and has already been documented in diverse bacterial species, including A. baumannii. Here, we report the first detection of a NDM-1-producing A. baumannii strain isolated in Benin. CASE PRESENTATION: A 31-year-old woman was admitted to a surgical unit with a diagnosis of post-cesarean hematoma. An extensively-drug resistant A. baumannii strain solely susceptible to amikacin, colistin and ciprofloxacin, and resistant to several other antibiotics including ceftazidime, imipenem, meropenem, gentamicin, tobramycin, ceftazidime/avibactam, and sulfamethoxazole-trimethoprim, was isolated from the wound. Production of NDM-1 was demonstrated by immunochromatographic testing. Whole genome sequencing of the isolate confirmed the presence of blaNDM-1, but also antibiotic resistance genes against multiple beta-lactamases and other classes of antibiotics, in addition to several virulence genes. Moreover, the blaNDM-1 gene was found to be present in a Tn125 transposon integrated on a plasmid. CONCLUSIONS: The discovery of this extensively-drug resistant A. baumannii strain carrying blaNDM-1 in Benin is worrying, especially because of its high potential risk of horizontal gene transfer due to being integrated into a transposon located on a plasmid. Strict control and prevention measures should be taken, once NDM-1 positive A. baumannii has been identified to prevent transfer of this resistance gene to other Enterobacterales. Capacity building is required by governmental agencies to provide suitable antibiotic treatment options and strategies, in combination with strengthening laboratory services for detection and surveillance of this pathogen.

IAMBEE: a web-service for the identification of adaptive pathways from parallel evolved clonal populations.

IAMBEE is a web server designed for the Identification of Adaptive Mutations in Bacterial Evolution Experiments (IAMBEE). Input data consist of genotype information obtained from independently evolved clonal populations or strains that show the same adapted behavior (phenotype). To distinguish adaptive from passenger mutations, IAMBEE searches for neighborhoods in an organism-specific interaction network that are recurrently mutated in the adapted populations. This search for recurrently mutated network neighborhoods, as proxies for pathways is driven by additional information on the functional impact of the observed genetic changes and their dynamics during adaptive evolution. In addition, the search explicitly accounts for the differences in mutation rate between the independently evolved populations. Using this approach, IAMBEE allows exploiting parallel evolution to identify adaptive pathways. The web-server is freely available at http://bioinformatics.intec.ugent.be/iambee/ with no login requirement.

Culture-Independent Analysis of Linuron-Mineralizing Microbiota and Functions in on-Farm Biopurification Systems via DNA-Stable Isotope Probing: Comparison with Enrichment Culture.

Our understanding of the microorganisms involved in in situ biodegradation of xenobiotics, like pesticides, in natural and engineered environments is poor. On-farm biopurification systems (BPSs) treat farm-produced pesticide-contaminated wastewater to reduce surface water pollution. BPSs are a labor and cost-efficient technology but are still mainly operated as black box systems. We used DNA-stable isotope probing (DNA-SIP) and classical enrichment to be informed about the organisms responsible for in situ degradation of the phenylurea herbicide linuron in a BPS matrix. DNA-SIP identified Ramlibacter, Variovorax, and an unknown Comamonadaceae genus as the dominant linuron assimilators. While linuron-degrading Variovorax strains have been isolated repeatedly, Ramlibacter has never been associated before with linuron degradation. Genes and mobile genetic elements (MGEs) previously linked to linuron catabolism were enriched in the heavy DNA-SIP fractions, suggesting their involvement in in situ linuron assimilation. BPS material free cultivation of linuron degraders from the same BPS matrix resulted in a community dominated by Variovorax, while Ramlibacter was not observed. Our study provides evidence for the role of Variovorax in in situ linuron biodegradation in a BPS, alongside other organisms like Ramlibacter, and further shows that cultivation results in a biased representation of the in situ linuron-assimilating bacterial populations.

A genoserotyping system for a fast and objective identification of Salmonella serotypes commonly isolated from poultry and pork food sectors in Belgium.

Humans are mostly contaminated by Salmonella through the consumption of pork- and poultry-derived food products. Therefore, a strict monitoring of Salmonella serotypes in food-producing animals is needed to limit the transmission of the pathogen to humans. Additionally, Salmonella can lead to economic loss in the food sector. Previously, a genoserotyping method using the MOL-PCR and Luminex technology was developed for the identification of the 6 Salmonella serotypes, and their variants, subjected to an official control in the Belgian food sector. In this study, 3 additional assays using the same technology were developed for the rapid and cost-effective detection of 13 dangerous highly invasive serotypes or other serotypes frequently isolated from the Belgian poultry and pork sector, i.e. Agona, Anatum, Brandenburg, Choleraesuis, Derby, Enteritidis vaccine strains, Gallinarum var. Gallinarum/Pullorum, Livingstone, Mbandaka, Minnesota, Ohio, Rissen and Senftenberg. Moreover, the previously developed first MOL-PCR assay was improved for S. Paratyphi B and serogroup O:3 detection. Finally, a Decision Support System hosted by a web application was created for an automatic and objective interpretation of the Luminex raw data. The 3 new assays and the modifications of the first assay were validated with a 100% accuracy, using 553 Salmonella and non-Salmonella strains in total.

A multiplex oligonucleotide ligation-PCR method for the genoserotyping of common Salmonella using a liquid bead suspension assay.

Salmonella is a major pathogen having a public health and economic impact in both humans and animals. Six serotypes of the Salmonella genus are mentioned in the Belgian and European regulation as to be rapidly excluded from the food chain (EU regulation N°2160/2003, Belgian royal decree 27/04/2017). The reference method for Salmonella serotyping, including slide-agglutination and biochemical tests, is time-consuming, expensive, not always objective, and therefore does not match the fast identification criteria required by the legislation. In this study, a molecular method, using genetic markers detected by Multiplex Oligonucleotide Ligation - PCR and Luminex technology, was developed for the identification of the 6 Salmonella serotypes and their variants subjected to an official control. The resulting method was validated with the analysis of 971 Salmonella isolated from different matrixes (human, animal, food or environment) and 33 non-Salmonella strains. The results were compared with the reference identifications, achieving an accuracy of 99.7%. The cost-effective high-throughput genoserotyping assay is performed in 1 day and generates objective results, thanks to the automatic interpretation of raw data using a barcode system. In conclusion, it is fully adapted to the implementation in first line laboratories and meets the requirements of the regulation.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing.

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

Strain-Level Metagenomic Data Analysis of Enriched In Vitro and In Silico Spiked Food Samples: Paving the Way towards a Culture-Free Foodborne Outbreak Investigation Using STEC as a Case Study.

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample.

Organellar carbon metabolism is coordinated with distinct developmental phases of secondary xylem.

Subcellular compartmentation of plant biosynthetic pathways in the mitochondria and plastids requires coordinated regulation of nuclear encoded genes, and the role of these genes has been largely ignored by wood researchers. In this study, we constructed a targeted systems genetics coexpression network of xylogenesis in Eucalyptus using plastid and mitochondrial carbon metabolic genes and compared the resulting clusters to the aspen xylem developmental series. The constructed network clusters reveal the organization of transcriptional modules regulating subcellular metabolic functions in plastids and mitochondria. Overlapping genes between the plastid and mitochondrial networks implicate the common transcriptional regulation of carbon metabolism during xylem secondary growth. We show that the central processes of organellar carbon metabolism are distinctly coordinated across the developmental stages of wood formation and are specifically associated with primary growth and secondary cell wall deposition. We also demonstrate that, during xylogenesis, plastid-targeted carbon metabolism is partially regulated by the central clock for carbon allocation towards primary and secondary xylem growth, and we discuss these networks in the context of previously established associations with wood-related complex traits. This study provides a new resolution into the integration and transcriptional regulation of plastid- and mitochondrial-localized carbon metabolism during xylogenesis.