aFold – using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data

Data normalization and identification of significant differential expression represent crucial steps in RNA-Seq analysis. Many available tools rely on assumptions that are often not met by real data, including the common assumption of symmetrical distribution of up- and down-regulated genes, the presence of only few differentially expressed genes and/or few outliers. Moreover, the cut-off for selecting significantly differentially expressed genes for further downstream analysis often depend on arbitrary choices

Experimental evolution of immunological specificity

Innate immune memory (i.e., immune priming) is found in many invertebrates. In some cases, immune priming provides protection against infection only when the same bacteria are used for priming and challenge; that is, priming can be specific. However, we still know little about the conditions favoring the evolution of immunological specificity. We present evidence that immune priming and its specificity can rapidly evolve in an insect through experimental selection by repeated bacterial exposure. Our populations evolved treatment-specific differences in expression profiles of immune, metabolic, and transcription-regulatory genes, pointing to similar mechanisms acting in vertebrate trained immunity. Hence, immune memory combines deeply rooted resemblances across systems with enormous evolutionary plasticity.Memory and specificity are hallmarks of the adaptive immune system. Contrary to prior belief, innate immune systems can also provide forms of immune memory, such as immune priming in invertebrates and trained immunity in vertebrates. Immune priming can even be specific but differs remarkably in cellular and molecular functionality from the well-studied adaptive immune system of vertebrates. To date, it is unknown whether and how the level of specificity in immune priming can adapt during evolution in response to natural selection. We tested the evolution of priming specificity in an invertebrate model, the beetle Tribolium castaneum. Using controlled evolution experiments, we selected beetles for either specific or unspecific immune priming toward the bacteria Pseudomonas fluorescens, Lactococcus lactis, and 4 strains of the entomopathogen Bacillus thuringiensis. After 14 generations of host selection, specificity of priming was not universally higher in the lines selected for specificity, but rather depended on the bacterium used for priming and challenge. The insect pathogen B. thuringiensis induced the strongest priming effect. Differences between the evolved populations were mirrored in the transcriptomic response, revealing involvement of immune, metabolic, and transcription-modifying genes. Finally, we demonstrate that the induction strength of a set of differentially expressed immune genes predicts the survival probability of the evolved lines upon infection. We conclude that high specificity of immune priming can evolve rapidly for certain bacteria, most likely due to changes in the regulation of immune genes

Alternative evolutionary paths to bacterial antibiotic resistance cause distinct collateral effects.

Published onlineJournal ArticleThis is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.When bacteria evolve resistance against a particular antibiotic, they may simultaneously gain increased sensitivity against a second one. Such collateral sensitivity may be exploited to develop novel, sustainable antibiotic treatment strategies aimed at containing the current, dramatic spread of drug resistance. To date, the presence and molecular basis of collateral sensitivity has only been studied in few bacterial species and is unknown for opportunistic human pathogens such as Pseudomonas aeruginosa. In the present study, we assessed patterns of collateral effects by experimentally evolving 160 independent populations of P. aeruginosa to high levels of resistance against eight commonly used antibiotics. The bacteria evolved resistance rapidly and expressed both collateral sensitivity and cross-resistance. The pattern of such collateral effects differed to those previously reported for other bacterial species, suggesting inter-specific differences in the underlying evolutionary trade-offs. Intriguingly, we also identified contrasting patterns of collateral sensitivity and cross-resistance among the replicate populations adapted to the same drug. Whole-genome sequencing of 81 independently evolved populations revealed distinct evolutionary paths of resistance to the selective drug, which determined whether bacteria became cross-resistant or collaterally sensitive towards others. Based on genomic and functional genetic analysis, we demonstrate that collateral sensitivity can result from resistance mutations in regulatory genes such as nalC or mexZ, which mediate aminoglycoside sensitivity in β-lactam-adapted populations, or the two-component regulatory system gene pmrB, which enhances penicillin sensitivity in gentamicin-resistant populations. Our findings highlight substantial variation in the evolved collateral effects among replicates, which in turn determine their potential in antibiotic therapy.We thank Anette Friedrichs, Lutz Becks, and the Schulenburg group for valuable advice and Melanie Vollstedt for technical support during genome sequencing. We are grateful for financial support from the German Science Foundation (DFG grant SCHU 1415/12-1) and the International Max-Planck Research School for Evolutionary Biology at the University of Kiel. We acknowledge infrastructural support by the DFG excellence cluster Inflammation at Interfaces

Cellular hysteresis as a principle to maximize the efficacy of antibiotic therapy

Rapid evolution is central to the current antibiotic crisis. Sustainable treatments must thus take account of the bacteria’s potential for adaptation. We identified cellular hysteresis as a principle to constrain bacterial evolution. Cellular hysteresis is a persistent change in bacterial physiology, reminiscent of cellular memory, which is induced by one antibiotic and enhances susceptibility toward another antibiotic. Cellular hysteresis increases bacterial extinction in fast sequential treatments and reduces selection of resistance by favoring responses specific to the induced physiological effects. Fast changes between antibiotics are key, because they create the continuously high selection conditions that are difficult to counter by bacteria. Our study highlights how an understanding of evolutionary processes can help to outsmart human pathogens.Antibiotic resistance has become one of the most dramatic threats to global health. While novel treatment options are urgently required, most attempts focus on finding new antibiotic substances. However, their development is costly, and their efficacy is often compromised within short time periods due to the enormous potential of microorganisms for rapid adaptation. Here, we developed a strategy that uses the currently available antibiotics. Our strategy exploits cellular hysteresis, which is the long-lasting, transgenerational change in cellular physiology that is induced by one antibiotic and sensitizes bacteria to another subsequently administered antibiotic. Using evolution experiments, mathematical modeling, genomics, and functional genetic analysis, we demonstrate that sequential treatment protocols with high levels of cellular hysteresis constrain the evolving bacteria by (i) increasing extinction frequencies, (ii) reducing adaptation rates, and (iii) limiting emergence of multidrug resistance. Cellular hysteresis is most effective in fast sequential protocols, in which antibiotics are changed within 12 h or 24 h, in contrast to the less frequent changes in cycling protocols commonly implemented in hospitals. We found that cellular hysteresis imposes specific selective pressure on the bacteria that disfavors resistance mutations. Instead, if bacterial populations survive, hysteresis is countered in two distinct ways, either through a process related to antibiotic tolerance or a mechanism controlled by the previously uncharacterized two-component regulator CpxS. We conclude that cellular hysteresis can be harnessed to optimize antibiotic therapy, to achieve both enhanced bacterial elimination and reduced resistance evolution

The genomic basis of rapid adaptation to antibiotic combination therapy in Pseudomonas aeruginosa

Combination therapy is a common antibiotic treatment strategy that aims at minimizing the risk of resistance evolution in several infectious diseases. Nonetheless, evidence supporting its efficacy against the nosocomial opportunistic pathogen Pseudomonas aeruginosa remains elusive. Identification of the possible evolutionary paths to resistance in multidrug environments can help to explain treatment outcome. For this purpose, we here performed whole-genome sequencing of 127 previously evolved populations of P. aeruginosa adapted to sublethal doses of distinct antibiotic combinations and corresponding single-drug treatments, and experimentally characterized several of the identified variants. We found that alterations in the regulation of efflux pumps are the most favored mechanism of resistance, regardless of the environment. Unexpectedly, we repeatedly identified intergenic variants in the adapted populations, often with no additional mutations and usually associated with genes involved in efflux pump expression, possibly indicating a regulatory function of the intergenic regions. The experimental analysis of these variants demonstrated that the intergenic changes caused similar increases in resistance against single and multidrug treatments as those seen for efflux regulatory gene mutants. Surprisingly, we could find no substantial fitness costs for a majority of these variants, most likely enhancing their competitiveness toward sensitive cells, even in antibiotic-free environments. We conclude that the regulation of efflux is a central target of antibiotic-mediated selection in P. aeruginosa and that, importantly, changes in intergenic regions may represent a usually neglected alternative process underlying bacterial resistance evolution, which clearly deserves further attention in the future

When the most potent combination of antibiotics selects for the greatest bacterial load: the Smile-Frown transition

Final published PDF version of article deposited in accordance with SHERPA RoMEO guidelinesConventional wisdom holds that the best way to treat infection with antibiotics is to ‘hit early and hit hard’. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessarily optimal? We combine mathematical modelling, evolution experiments, whole genome sequencing and genetic manipulation of a resistance mechanism to demonstrate that deploying synergistic antibiotics can, in practice, be the worst strategy if bacterial clearance is not achieved after the first treatment phase. As treatment proceeds, it is only to be expected that the strength of antibiotic synergy will diminish as the frequency of drug-resistant bacteria increases. Indeed, antibiotic efficacy decays exponentially in our five-day evolution experiments. However, as the theory of competitive release predicts, drug-resistant bacteria replicate fastest when their drug-susceptible competitors are eliminated by overly-aggressive treatment. Here, synergy exerts such strong selection for resistance that an antagonism consistently emerges by day 1 and the initially most aggressive treatment produces the greatest bacterial load, a fortiori greater than if just one drug were given. Whole genome sequencing reveals that such rapid evolution is the result of the amplification of a genomic region containing four drug-resistance mechanisms, including the acrAB efflux operon. When this operon is deleted in genetically manipulated mutants and the evolution experiment repeated, antagonism fails to emerge in five days and antibiotic synergy is maintained for longer. We therefore conclude that unless super-inhibitory doses are achieved and maintained until the pathogen is successfully cleared, synergistic antibiotics can have the opposite effect to that intended by helping to increase pathogen load where, and when, the drugs are found at sub-inhibitory concentrations

Dietary history contributes to enterotype-like clustering and functional metagenomic content in the intestinal microbiome of wild mice

Understanding the origins of gut microbial community structure is critical for the identification and interpretation of potential fitnessrelated traits for the host. The presence of community clusters characterized by differences in the abundance of signature taxa, referred to as enterotypes, is a debated concept first reported in humans and later extended to other mammalian hosts. In this study, we provide a thorough assessment of their existence in wild house mice using a panel of evaluation criteria.We identify support for two clusters that are compositionally similar to clusters identified in humans, chimpanzees, and laboratory mice, characterized by differences in Bacteroides, Robinsoniella, and unclassified genera belonging to the family Lachnospiraceae. To further evaluate these clusters, we (i) monitored community changes associated with moving mice from the natural to a laboratory environment, (ii) performed functional metagenomic sequencing, and (iii) subjected wild-caught samples to stable isotope analysis to reconstruct dietary patterns. This process reveals differences in the proportions of genes involved in carbohydrate versus protein metabolism in the functional metagenome, as well as differences in plant- versus meat-derived food sources between clusters. In conjunction with wild-caught mice quickly changing their enterotype classification upon transfer to a standard laboratory chow diet, these results provide strong evidence that dietary history contributes to the presence of enterotype-like clustering in wild mice

Screening of human gene promoter activities using transfected-cell arrays

Promoters are the best characterized transcriptional regulatory sequences in complex genomes because of their predictable location immediately upstream of transcription start sites. Despite a substantial body of literature describing transcriptional promoters, the identification of true start sites for all human transcripts is far from complete. The same is true of the key structural and functional elements responsible for promoter action in different cell types. In order to identify elements responsible for promoter activity, we applied transfected-cell array technology to functionally evaluate promoters for genes involved in inflammatory bowel disease. Seventy-four promoters were examined by reverse transfection of a promoter-fluorescent reporter constructs into a human embryonic kidney cell line (HEK293T). Sixteen (21.6%) promoters were found to be active in HEK293 T cells. Correlations between promoter activity and endogenous transcript level were calculated, and 75% of active promoters were found to be associated with transcriptional activity of their gene counterparts. These results provide experimental evidence of promoter activity, which may aid in understanding the regulation of gene expression. Moreover, this is the first large-scale functional study of regulatory sequences to use a high-throughput transfected-cell array technique

Multiscale heterogeneity in gastric adenocarcinoma evolution is an obstacle to precision medicine

Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer expansion, in which tumor subclones are not evenly mixed during tumor progression but rather spatially separated and diversified. We hypothesize that precision medicine efforts are compromised when clinical decisions are based on a single-sample analysis, which ignores the mechanisms of cancer evolution and resulting intratumoral heterogeneity. Using multiregional whole-exome sequencing, we investigated the effect of somatic evolution on intratumoral heterogeneity aiming to shed light on the evolutionary biology of GC

A functional methylome map of ulcerative colitis

The etiology of inflammatory bowel diseases is only partially explained by the current genetic risk map. It is hypothesized that environmental factors modulate the epigenetic landscape and thus contribute to disease susceptibility, manifestation, and progression. To test this, we analyzed DNA methylation (DNAm), a fundamental mechanism of epigenetic long-term modulation of gene expression. We report a three-layer epigenome-wide association study (EWAS) using intestinal biopsies from 10 monozygotic twin pairs (n = 20 individuals) discordant for manifestation of ulcerative colitis (UC). Genome-wide expression scans were generated using Affymetrix UG 133 Plus 2.0 arrays (layer 1). Genome-wide DNAm scans were carried out using Illumina 27k Infinium Bead Arrays to identify methylation variable positions (MVPs, layer 2), and MeDIP-chip on Nimblegen custom 385k Tiling Arrays to identify differentially methylated regions (DMRs, layer 3). Identified MVPs and DMRs were validated in two independent patient populations by quantitative real-time PCR and bisulfite-pyrosequencing (n = 185). The EWAS identified 61 disease-associated loci harboring differential DNAm in cis of a differentially expressed transcript. All constitute novel candidate risk loci for UC not previously identified by GWAS. Among them are several that have been functionally implicated in inflammatory processes, e.g., complement factor CFI, the serine protease inhibitor SPINK4, and the adhesion molecule THY1 (also known as CD90). Our study design excludes nondisease inflammation as a cause of the identified changes in DNAm. This study represents the first replicated EWAS of UC integrated with transcriptional signatures in the affected tissue and demonstrates the power of EWAS to uncover unexplained disease risk and molecular events of disease manifestation