Interdisciplinary Analyses of Bronze Age Communities from Western Hungary Reveal Complex Population Histories.

In this study, we report 21 ancient shotgun genomes from present-day Western Hungary, from previously understudied Late Copper Age Baden, and Bronze Age Somogyvár-Vinkovci, Kisapostag, and Encrusted Pottery archeological cultures (3,530-1,620 cal Bce). Our results indicate the presence of high steppe ancestry in the Somogyvár-Vinkovci culture. They were then replaced by the Kisapostag group, who exhibit an outstandingly high (up to ∼47%) Mesolithic hunter-gatherer ancestry, despite this component being thought to be highly diluted by the time of the Early Bronze Age. The Kisapostag population contributed the genetic basis for the succeeding community of the Encrusted Pottery culture. We also found an elevated hunter-gatherer component in a local Baden culture-associated individual, but no connections were proven to the Bronze Age individuals. The hunter-gatherer ancestry in Kisapostag is likely derived from two main sources, one from a Funnelbeaker or Globular Amphora culture-related population and one from a previously unrecognized source in Eastern Europe. We show that this ancestry not only appeared in various groups in Bronze Age Central Europe but also made contributions to Baltic populations. The social structure of Kisapostag and Encrusted Pottery cultures is patrilocal, similarly to most contemporaneous groups. Furthermore, we developed new methods and method standards for computational analyses of ancient DNA, implemented to our newly developed and freely available bioinformatic package. By analyzing clinical traits, we found carriers of aneuploidy and inheritable genetic diseases. Finally, based on genetic and anthropological data, we present here the first female facial reconstruction from the Bronze Age Carpathian Basin.

SignaLink3: a multi-layered resource to uncover tissue-specific signaling networks.

Signaling networks represent the molecular mechanisms controlling a cell's response to various internal or external stimuli. Most currently available signaling databases contain only a part of the complex network of intertwining pathways, leaving out key interactions or processes. Hence, we have developed SignaLink3 (http://signalink.org/), a value-added knowledge-base that provides manually curated data on signaling pathways and integrated data from several types of databases (interaction, regulation, localisation, disease, etc.) for humans, and three major animal model organisms. SignaLink3 contains over 400 000 newly added human protein-protein interactions resulting in a total of 700 000 interactions for Homo sapiens, making it one of the largest integrated signaling network resources. Next to H. sapiens, SignaLink3 is the only current signaling network resource to provide regulatory information for the model species Caenorhabditis elegans and Danio rerio, and the largest resource for Drosophila melanogaster. Compared to previous versions, we have integrated gene expression data as well as subcellular localization of the interactors, therefore uniquely allowing tissue-, or compartment-specific pathway interaction analysis to create more accurate models. Data is freely available for download in widely used formats, including CSV, PSI-MI TAB or SQL.

Discovering cooperative biomarkers for heterogeneous complex disease diagnoses.

Biomarkers with high reproducibility and accurate prediction performance can contribute to comprehending the underlying pathogenesis of related complex diseases and further facilitate disease diagnosis and therapy. Techniques integrating gene expression profiles and biological networks for the identification of network-based disease biomarkers are receiving increasing interest. The biomarkers for heterogeneous diseases often exhibit strong cooperative effects, which implies that a set of genes may achieve more accurate outcome prediction than any single gene. In this study, we evaluated various biomarker identification methods that consider gene cooperative effects implicitly or explicitly, and proposed the gene cooperation network to explicitly model the cooperative effects of gene combinations. The gene cooperation network-enhanced method, named as MarkRank, achieves superior performance compared with traditional biomarker identification methods in both simulation studies and real data sets. The biomarkers identified by MarkRank not only have a better prediction accuracy but also have stronger topological relationships in the biological network and exhibit high specificity associated with the related diseases. Furthermore, the top genes identified by MarkRank involve crucial biological processes of related diseases and give a good prioritization for known disease genes. In conclusion, MarkRank suggests that explicit modeling of gene cooperative effects can greatly improve biomarker identification for complex diseases, especially for diseases with high heterogeneity.

Directed evolution of multiple genomic loci allows the prediction of antibiotic resistance.

Antibiotic development is frequently plagued by the rapid emergence of drug resistance. However, assessing the risk of resistance development in the preclinical stage is difficult. Standard laboratory evolution approaches explore only a small fraction of the sequence space and fail to identify exceedingly rare resistance mutations and combinations thereof. Therefore, new rapid and exhaustive methods are needed to accurately assess the potential of resistance evolution and uncover the underlying mutational mechanisms. Here, we introduce directed evolution with random genomic mutations (DIvERGE), a method that allows an up to million-fold increase in mutation rate along the full lengths of multiple predefined loci in a range of bacterial species. In a single day, DIvERGE generated specific mutation combinations, yielding clinically significant resistance against trimethoprim and ciprofloxacin. Many of these mutations have remained previously undetected or provide resistance in a species-specific manner. These results indicate pathogen-specific resistance mechanisms and the necessity of future narrow-spectrum antibacterial treatments. In contrast to prior claims, we detected the rapid emergence of resistance against gepotidacin, a novel antibiotic currently in clinical trials. Based on these properties, DIvERGE could be applicable to identify less resistance-prone antibiotics at an early stage of drug development. Finally, we discuss potential future applications of DIvERGE in synthetic and evolutionary biology.

Effects of bowel cleansing on the composition of the gut microbiota in inflammatory bowel disease patients and healthy controls.

Background: In patients with inflammatory bowel disease (IBD), Crohn's disease (CD), and ulcerative colitis (UC), numerous cases of exacerbations could be observed after colonoscopy, raising the possible pathogenetic effect of colonic microbiota alterations in IBD flare. Objectives: We aimed to investigate the changes in the fecal microbiota composition in IBD patients influenced by the bowel preparation with sodium picosulfate. Design: We enrolled patients with IBD undergoing bowel preparation for colonoscopy in the prospective cohort study. The control group (Con) comprised non-IBD patients who underwent colonoscopy. Clinical data, blood, and stool samples were collected before colonoscopy (timepoint A), 3 days later (timepoint B), and 4 weeks later (timepoint C). Methods: Disease activity and gut microbiota changes were assessed at each timepoint. Fecal microbiota structure - at family level - was determined by sequencing the V4 region of the 16S rRNA gene. Statistical analysis included differential abundance analysis and Mann-Whitney tests. Results: Forty-one patients (9 CD, 13 UC, and 19 Con) were included. After bowel preparation, alpha diversity was lower in the CD group than in the UC (p = 0.01) and Con (p = 0.02) groups at timepoint B. Alpha diversity was significantly higher in the UC group than in the CD and Con (p = 0.03) groups at timepoint C. Beta diversity difference differed between the IBD and Con (p = 0.001) groups. Based on the differential abundance analysis, the Clostridiales family was increased, whereas the Bifidobacteriaceae family was decreased in CD patients compared to the Con at timepoint B. Conclusions: Bowel preparation may change the fecal microbial composition in IBD patients, which may have a potential role in disease exacerbation after bowel cleansing.

Downregulation of transposable elements extends lifespan in Caenorhabditis elegans.

Mobility of transposable elements (TEs) frequently leads to insertional mutations in functional DNA regions. In the potentially immortal germline, TEs are effectively suppressed by the Piwi-piRNA pathway. However, in the genomes of ageing somatic cells lacking the effects of the pathway, TEs become increasingly mobile during the adult lifespan, and their activity is associated with genomic instability. Whether the progressively increasing mobilization of TEs is a cause or a consequence of ageing remains a fundamental problem in biology. Here we show that in the nematode Caenorhabditis elegans, the downregulation of active TE families extends lifespan. Ectopic activation of Piwi proteins in the soma also promotes longevity. Furthermore, DNA N6-adenine methylation at TE stretches gradually rises with age, and this epigenetic modification elevates their transcription as the animal ages. These results indicate that TEs represent a novel genetic determinant of ageing, and that N6-adenine methylation plays a pivotal role in ageing control.

Comparison of Boolean analysis and standard phylogenetic methods using artificially evolved and natural mt-tRNA sequences from great apes.

Boolean analysis (or BOOL-AN; Jakó et al., 2009. BOOL-AN: A method for comparative sequence analysis and phylogenetic reconstruction. Mol. Phylogenet. Evol. 52, 887-97.), a recently developed method for sequence comparison uses the Iterative Canonical Form of Boolean functions. It considers sequence information in a way entirely different from standard phylogenetic methods (i.e. Maximum Parsimony, Maximum-Likelihood, Neighbor-Joining, and Bayesian analysis). The performance and reliability of Boolean analysis were tested and compared with the standard phylogenetic methods, using artificially evolved - simulated - nucleotide sequences and the 22 mitochondrial tRNA genes of the great apes. At the outset, we assumed that the phylogeny of Hominidae is generally well established, and the guide tree of artificial sequence evolution can also be used as a benchmark. These offer a possibility to compare and test the performance of different phylogenetic methods. Trees were reconstructed by each method from 2500 simulated sequences and 22 mitochondrial tRNA sequences. We also introduced a special re-sampling method for Boolean analysis on permuted sequence sites, the P-BOOL-AN procedure. Considering the reliability values (branch support values of consensus trees and Robinson-Foulds distances) we used for simulated sequence trees produced by different phylogenetic methods, BOOL-AN appeared as the most reliable method. Although the mitochondrial tRNA sequences of great apes are relatively short (59-75 bases long) and the ratio of their constant characters is about 75%, BOOL-AN, P-BOOL-AN and the Bayesian approach produced the same tree-topology as the established phylogeny, while the outcomes of Maximum Parsimony, Maximum-Likelihood and Neighbor-Joining methods were equivocal. We conclude that Boolean analysis is a promising alternative to existing methods of sequence comparison for phylogenetic reconstruction and congruence analysis.

TFLink: an integrated gateway to access transcription factor-target gene interactions for multiple species.

Analysis of transcriptional regulatory interactions and their comparisons across multiple species are crucial for progress in various fields in biology, from functional genomics to the evolution of signal transduction pathways. However, despite the rapidly growing body of data on regulatory interactions in several eukaryotes, no databases exist to provide curated high-quality information on transcription factor-target gene interactions for multiple species. Here, we address this gap by introducing the TFLink gateway, which uniquely provides experimentally explored and highly accurate information on transcription factor-target gene interactions (∼12 million), nucleotide sequences and genomic locations of transcription factor binding sites (∼9 million) for human and six model organisms: mouse, rat, zebrafish, fruit fly, worm and yeast by integrating 10 resources. TFLink provides user-friendly access to data on transcription factor-target gene interactions, interactive network visualizations and transcription factor binding sites, with cross-links to several other databases. Besides containing accurate information on transcription factors, with a clear labelling of the type/volume of the experiments (small-scale or high-throughput), the source database and the original publications, TFLink also provides a wealth of standardized regulatory data available for download in multiple formats. The database offers easy access to high-quality data for wet-lab researchers, supplies data for gene set enrichment analyses and facilitates systems biology and comparative gene regulation studies. Database URL https://tflink.net/.

A single early introduction governed viral diversity in the second wave of SARS-CoV-2 epidemic in Hungary.

Retrospective evaluation of past waves of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic is key for designing optimal interventions against future waves and novel pandemics. Here, we report on analysing genome sequences of SARS-CoV-2 from the first two waves of the epidemic in 2020 in Hungary, mirroring a suppression and a mitigation strategy, respectively. Our analysis reveals that the two waves markedly differed in viral diversity and transmission patterns. Specifically, unlike in several European areas or in the USA, we have found no evidence for early introduction and cryptic transmission of the virus in the first wave of the pandemic in Hungary. Despite the introduction of multiple viral lineages, extensive community spread was prevented by a timely national lockdown in March 2020. In sharp contrast, the majority of the cases in the much larger second wave can be linked to a single transmission lineage of the pan-European B.1.160 variant. This lineage was introduced unexpectedly early, followed by a 2-month-long cryptic transmission before a soar of detected cases in September 2020. Epidemic analysis has revealed that the dominance of this lineage in the second wave was not associated with an intrinsic transmission advantage. This finding is further supported by the rapid replacement of B.1.160 by the alpha variant (B.1.1.7) that launched the third wave of the epidemic in February 2021. Overall, these results illustrate how the founder effect in combination with the cryptic transmission, instead of repeated international introductions or higher transmissibility, can govern viral diversity.

The C. elegans Hox gene ceh-13 regulates cell migration and fusion in a non-colinear way. Implications for the early evolution of Hox clusters.

BACKGROUND: Hox genes play a central role in axial patterning during animal development. They are clustered in the genome and specify cell fate in sequential domains along the anteroposterior (A-P) body axis in a conserved order that is co-linear with their relative genomic position. In the soil worm Caenorhabditis elegans, this striking rule of co-linearity is broken by the anterior Hox gene ceh-13, which is located between the two middle Hox paralogs, lin-39 and mab-5, within the loosely organized nematode Hox cluster. Despite its evolutionary and developmental significance, the functional consequence of this unusual genomic organization remains unresolved. RESULTS: In this study we have investigated the role of ceh-13 in different developmental processes, and found that its expression and function are not restricted to the anterior body part. We show that ceh-13 affects cell migration and fusion as well as tissue patterning in the middle and posterior body regions too. These data reveal novel roles for ceh-13 in developmental processes known to be under the control of middle Hox paralogs. Consistently, enhanced activity of lin-39 and mab-5 can suppress developmental arrest and morphologic malformation in ceh-13 deficient animals. CONCLUSION: Our findings presented here show that, unlike other Hox genes in C. elegans which display region-specific accumulation and function along the A-P axis, the expression and functional domain of the anterior Hox paralog ceh-13 extends beyond the anterior region of the worm. Furthermore, ceh-13 and the middle Hox paralogs share several developmental functions. Together, these results suggest the emergence of the middle-group Hox genes from a ceh-13-like primordial Hox ancestor.

Functional Anatomical Changes in Ulcerative Colitis Patients Determine Their Gut Microbiota Composition and Consequently the Possible Treatment Outcome.

Gut microbial composition alters in some special situations, such as in ulcerative colits (UC) after total proctocolectomy and ileal pouch-anal anastomosis (IPAA) surgery. The aim of our study was to determine the composition of the intestinal microbiome in UC patients after IPAA surgery, compared with UC patients, familial adenomatous polyposis (FAP) patients after IPAA surgery and healthy controls. Clinical data of patients, blood and faecal samples were collected. Faecal microbiota structure was determined by sequencing the V4 hypervariable region of the 16S rRNA gene. Overall, 56 patients were enrolled. Compared to the Healthy group, both the Pouch active and UC active groups had higher Enterobacteriaceae, Enterococcaceae and Pasteurellaceae abundance. The Pouch and UC groups showed distinct separation based on their alpha and beta bacterial diversities. The UC group had higher Prevotellaceae, Rikenellaceae, Ruminococcaceae abundance compared to the Pouch active group. Pouch and FAP participants showed similar bacterial community composition. There was no significant difference in the bacterial abundance between the active and inactive subgroups of the Pouch or UC groups. Gut microbiome and anatomical status together construct a functional unit that has influence on diversity, in addition to intestinal inflammation that is a part of the pathomechanism in UC.

BOOL-AN: a method for comparative sequence analysis and phylogenetic reconstruction.

A novel discrete mathematical approach is proposed as an additional tool for molecular systematics which does not require prior statistical assumptions concerning the evolutionary process. The method is based on algorithms generating mathematical representations directly from DNA/RNA or protein sequences, followed by the output of numerical (scalar or vector) and visual characteristics (graphs). The binary encoded sequence information is transformed into a compact analytical form, called the Iterative Canonical Form (or ICF) of Boolean functions, which can then be used as a generalized molecular descriptor. The method provides raw vector data for calculating different distance matrices, which in turn can be analyzed by neighbor-joining or UPGMA to derive a tree, or by principal coordinates analysis to get an ordination scattergram. The new method and the associated software for inferring phylogenetic trees are called the Boolean analysis or BOOL-AN.

Targeted interplay between bacterial pathogens and host autophagy.

Due to the critical role played by autophagy in pathogen clearance, pathogens have developed diverse strategies to subvert it. Despite previous key findings of bacteria-autophagy interplay, asystems-level insight into selective targeting by the host and autophagy modulation by the pathogens is lacking. We predicted potential interactions between human autophagy proteins and effector proteins from 56 pathogenic bacterial species by identifying bacterial proteins predicted to have recognition motifs for selective autophagy receptors SQSTM1/p62, CALCOCO2/NDP52 and MAP1LC3/LC3. Using structure-based interaction prediction, we identified bacterial proteins capable to modify core autophagy components. Our analysis revealed that autophagy receptors in general potentially target mostly genus-specific proteins, and not those present in multiple genera. The complementarity between the predicted SQSTM1/p62 and CALCOCO2/NDP52 targets, which has been shown for Salmonella, Listeria and Shigella, could be observed across other pathogens. This complementarity potentially leaves the host more susceptible to chronic infections upon the mutation of autophagy receptors. Proteins derived from enterotoxigenic and non-toxigenic Bacillus outer membrane vesicles indicated that autophagy targets pathogenic proteins rather than non-pathogenic ones. We also observed apathogen-specific pattern as to which autophagy phase could be modulated by specific genera. We found intriguing examples of bacterial proteins that could modulate autophagy, and in turn being targeted by autophagy as ahost defense mechanism. We confirmed experimentally an interplay between a Salmonella protease, YhjJ and autophagy. Our comparative meta-analysis points out key commonalities and differences in how pathogens could affect autophagy and how autophagy potentially recognizes these pathogenic effectors. Abbreviations: ATG5: autophagy related 5; CALCOCO2/NDP52: calcium binding and coiled-coil domain 2; GST: glutathione S-transferase; LIR: MAP1LC3/LC3-interacting region; MAP1LC3/LC3: microtubule associated protein 1 light chain 3 alpha; OMV: outer membrane vesicles; SQSTM1/p62: sequestosome 1; SCV: Salmonella containing vesicle; TECPR1: tectonin beta-propeller repeat containing 1; YhjJ: hypothetical zinc-protease.

Chemical-genetic profiling reveals limited cross-resistance between antimicrobial peptides with different modes of action.

Antimicrobial peptides (AMPs) are key effectors of the innate immune system and promising therapeutic agents. Yet, knowledge on how to design AMPs with minimal cross-resistance to human host-defense peptides remains limited. Here, we systematically assess the resistance determinants of Escherichia coli against 15 different AMPs using chemical-genetics and compare to the cross-resistance spectra of laboratory-evolved AMP-resistant strains. Although generalizations about AMP resistance are common in the literature, we find that AMPs with different physicochemical properties and cellular targets vary considerably in their resistance determinants. As a consequence, cross-resistance is prevalent only between AMPs with similar modes of action. Finally, our screen reveals several genes that shape susceptibility to membrane- and intracellular-targeting AMPs in an antagonistic manner. We anticipate that chemical-genetic approaches could inform future efforts to minimize cross-resistance between therapeutic and human host AMPs.

Phylogenetic barriers to horizontal transfer of antimicrobial peptide resistance genes in the human gut microbiota.

The human gut microbiota has adapted to the presence of antimicrobial peptides (AMPs), which are ancient components of immune defence. Despite its medical importance, it has remained unclear whether AMP resistance genes in the gut microbiome are available for genetic exchange between bacterial species. Here, we show that AMP resistance and antibiotic resistance genes differ in their mobilization patterns and functional compatibilities with new bacterial hosts. First, whereas AMP resistance genes are widespread in the gut microbiome, their rate of horizontal transfer is lower than that of antibiotic resistance genes. Second, gut microbiota culturing and functional metagenomics have revealed that AMP resistance genes originating from phylogenetically distant bacteria have only a limited potential to confer resistance in Escherichia coli, an intrinsically susceptible species. Taken together, functional compatibility with the new bacterial host emerges as a key factor limiting the genetic exchange of AMP resistance genes. Finally, our results suggest that AMPs induce highly specific changes in the composition of the human microbiota, with implications for disease risks.

SalmoNet, an integrated network of ten Salmonella enterica strains reveals common and distinct pathways to host adaptation.

Salmonella enterica is a prominent bacterial pathogen with implications on human and animal health. Salmonella serovars could be classified as gastro-intestinal or extra-intestinal. Genome-wide comparisons revealed that extra-intestinal strains are closer relatives of gastro-intestinal strains than to each other indicating a parallel evolution of this trait. Given the complexity of the differences, a systems-level comparison could reveal key mechanisms enabling extra-intestinal serovars to cause systemic infections. Accordingly, in this work, we introduce a unique resource, SalmoNet, which combines manual curation, high-throughput data and computational predictions to provide an integrated network for Salmonella at the metabolic, transcriptional regulatory and protein-protein interaction levels. SalmoNet provides the networks separately for five gastro-intestinal and five extra-intestinal strains. As a multi-layered, multi-strain database containing experimental data, SalmoNet is the first dedicated network resource for Salmonella. It comprehensively contains interactions between proteins encoded in Salmonella pathogenicity islands, as well as regulatory mechanisms of metabolic processes with the option to zoom-in and analyze the interactions at specific loci in more detail. Application of SalmoNet is not limited to strain comparisons as it also provides a Salmonella resource for biochemical network modeling, host-pathogen interaction studies, drug discovery, experimental validation of novel interactions, uncovering new pathological mechanisms from emergent properties and epidemiological studies. SalmoNet is available at http://salmonet.org.

Identification of critical paralog groups with indispensable roles in the regulation of signaling flow.

Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and 'bowtieness' when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis.

Starvation-response may not involve Atg1-dependent autophagy induction in non-unikont parasites.

Autophagy, the lysosome-mediated self-degradation process, is implicated in survival during starvation in yeast, Dictyostelium and animals. In these eukaryotic taxa (collectively called Unikonts), autophagy is induced primarily through the Atg1/ULK1 complex in response to nutrient depletion. Autophagy has also been well-studied in non-unikont parasites, such as Trypanosoma and Plasmodium, and found important in their life-cycle transitions. However, how autophagy is induced in non-unikonts remains largely unrevealed. Using a bioinformatics approach, we examined the presence of Atg1 and of its complex in the genomes of 40 non-unikonts. We found that these genomes do not encode typical Atg1 proteins: BLAST and HMMER queries matched only with the kinase domain of Atg1, while other segments responsible for regulation and protein-binding were missing. Non-unikonts also lacked other components of the Atg1-inducing complex. Orthologs of an alternative autophagy inducer, Atg6 were found only in the half of the species, indicating that the other half may possess other inducing mechanisms. As key autophagy genes have differential expression patterns during life-cycle, we raise the possibility that autophagy in these protists is induced mainly at the post-transcriptional level. Understanding Atg1-independent autophagy induction mechanisms in these parasites may lead to novel pharmacological interventions, not affecting human Atg1-dependent autophagy.