Solving genomic puzzles: computational methods for metagenomic binning.

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

Antiviral and Anti-Inflammatory Therapeutic Effect of RAGE-Ig Protein against Multiple SARS-CoV-2 Variants of Concern Demonstrated in K18-hACE2 Mouse and Syrian Golden Hamster Models.

SARS-CoV-2 variants of concern (VOCs) continue to evolve and reemerge with chronic inflammatory long COVID sequelae, necessitating the development of anti-inflammatory therapeutic molecules. Therapeutic effects of the receptor for advanced glycation end products (RAGE) were reported in many inflammatory diseases. However, a therapeutic effect of RAGE in COVID-19 has not been reported. In the present study, we investigated whether and how the RAGE-Ig fusion protein would have an antiviral and anti-inflammatory therapeutic effect in the COVID-19 system. The protective therapeutic effect of RAGE-Ig was determined in vivo in K18-hACE2 transgenic mice and Syrian golden hamsters infected with six VOCs of SARS-CoV-2. The underlying antiviral mechanism of RAGE-Ig was determined in vitro in SARS-CoV-2-infected human lung epithelial cells (BEAS-2B). Following treatment of K18-hACE2 mice and hamsters infected with various SARS-CoV-2 VOCs with RAGE-Ig, we demonstrated (1) significant dose-dependent protection (i.e., greater survival, less weight loss, lower virus replication in the lungs); (2) a reduction of inflammatory macrophages (F4/80+/Ly6C+) and neutrophils (CD11b+/Ly6G+) infiltrating the infected lungs; (3) a RAGE-Ig dose-dependent increase in the expression of type I IFNs (IFN-α and IFN-ß) and type III IFN (IFNλ2) and a decrease in the inflammatory cytokines (IL-6 and IL-8) in SARS-CoV-2-infected human lung epithelial cells; and (4) a dose-dependent decrease in the expression of CD64 (FcgR1) on monocytes and lung epithelial cells from symptomatic COVID-19 patients. Our preclinical findings revealed type I and III IFN-mediated antiviral and anti-inflammatory therapeutic effects of RAGE-Ig protein against COVID-19 caused by multiple SARS-CoV-2 VOCs.

PRFect: a tool to predict programmed ribosomal frameshifts in prokaryotic and viral genomes.

BACKGROUND: One of the stranger phenomena that can occur during gene translation is where, as a ribosome reads along the mRNA, various cellular and molecular properties contribute to stalling the ribosome on a slippery sequence and shifting the ribosome into one of the other two alternate reading frames. The alternate frame has different codons, so different amino acids are added to the peptide chain. More importantly, the original stop codon is no longer in-frame, so the ribosome can bypass the stop codon and continue to translate the codons past it. This produces a longer version of the protein, a fusion of the original in-frame amino acids, followed by all the alternate frame amino acids. There is currently no automated software to predict the occurrence of these programmed ribosomal frameshifts (PRF), and they are currently only identified by manual curation. RESULTS: Here we present PRFect, an innovative machine-learning method for the detection and prediction of PRFs in coding genes of various types. PRFect combines advanced machine learning techniques with the integration of multiple complex cellular properties, such as secondary structure, codon usage, ribosomal binding site interference, direction, and slippery site motif. Calculating and incorporating these diverse properties posed significant challenges, but through extensive research and development, we have achieved a user-friendly approach. The code for PRFect is freely available, open-source, and can be easily installed via a single command in the terminal. Our comprehensive evaluations on diverse organisms, including bacteria, archaea, and phages, demonstrate PRFect's strong performance, achieving high sensitivity, specificity, and an accuracy exceeding 90%. The code for PRFect is freely available and installs with a single terminal command. CONCLUSION: PRFect represents a significant advancement in the field of PRF detection and prediction, offering a powerful tool for researchers and scientists to unravel the intricacies of programmed ribosomal frameshifting in coding genes.

Phables: from fragmented assemblies to high-quality bacteriophage genomes.

MOTIVATION: Microbial communities have a profound impact on both human health and various environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of challenges in viral assembly, fragmentation of genomes can occur, and existing tools may recover incomplete genome fragments. Therefore, the identification and characterization of novel phage genomes remain a challenge, leading to the need of improved approaches for phage genome recovery. RESULTS: We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. AVAILABILITY AND IMPLEMENTATION: Phables is available on GitHub at https://github.com/Vini2/phables.

Knowing and Naming: Phage Annotation and Nomenclature for Phage Therapy.

Bacteriophages, or phages, are viruses that infect bacteria shaping microbial communities and ecosystems. They have gained attention as potential agents against antibiotic resistance. In phage therapy, lytic phages are preferred for their bacteria killing ability, while temperate phages, which can transfer antibiotic resistance or toxin genes, are avoided. Selection relies on plaque morphology and genome sequencing. This review outlines annotating genomes, identifying critical genomic features, and assigning functional labels to protein-coding sequences. These annotations prevent the transfer of unwanted genes, such as antimicrobial resistance or toxin genes, during phage therapy. Additionally, it covers International Committee on Taxonomy of Viruses (ICTV)-an established phage nomenclature system for simplified classification and communication. Accurate phage genome annotation and nomenclature provide insights into phage-host interactions, replication strategies, and evolution, accelerating our understanding of the diversity and evolution of phages and facilitating the development of phage-based therapies.

Hypertrophic and fibrotic human PKD hearts are associated with macrophage infiltration and abnormal TGF-ß1 signaling.

Autosomal dominant polycystic kidney disease (PKD) is a hereditary kidney disorder which can affect cardiovascular system. Cardiac hypertrophy and cardiomyopathy in PKD have been reported by echocardiography analyses, but histopathology analyses of human PKD hearts have never been examined. The current studies evaluated human heart tissues from five subjects without PKD (non-PKD) and five subjects with PKD. Our histopathology data of human PKD hearts showed an increased extracellular matrix associated with cardiac hypertrophy and fibrosis. Hypertrophy- and fibrosis-associated pathways involving abnormal cardiac structure were next analyzed. We found that human PKD myocardium was infiltrated by inflammatory macrophage M1 and M2; expression of transforming growth factor (TGF-ß1) and its receptor were upregulated with overexpression of pSmad3 and ß-catenin. Because patients with PKD have an abnormal kidney function that could potentially affect heart structure, we used a heart-specific PKD mouse model to validate that cardiac hypertrophy and fibrosis were independent from polycystic kidney. In summary, our data show that hearts from human PKD were characterized by hypertrophy, interstitial fibrosis, perivascular fibrosis, and conduction system fibrosis with upregulated TGF-ß1 and its receptor. We suggest that such structural abnormalities may predispose to systolic and diastolic cardiac dysfunction in the PKD myocardium.

Dual roles of myocardial mitochondrial AKT on diabetic cardiomyopathy and whole body metabolism.

BACKGROUND: The PI3K/AKT pathway transduces the majority of the metabolic actions of insulin. In addition to cytosolic targets, insulin-stimulated phospho-AKT also translocates to mitochondria in the myocardium. Mouse models of diabetes exhibit impaired mitochondrial AKT signaling but the implications of this on cardiac structure and function is unknown. We hypothesized that loss of mitochondrial AKT signaling is a critical step in cardiomyopathy and reduces cardiac oxidative phosphorylation. METHODS: To focus our investigation on the pathophysiological consequences of this mitochondrial signaling pathway, we generated transgenic mouse models of cardiac-specific, mitochondria-targeting, dominant negative AKT1 (CAMDAKT) and constitutively active AKT1 expression (CAMCAKT). Myocardial structure and function were examined using echocardiography, histology, and biochemical assays. We further investigated the underlying effects of mitochondrial AKT1 on mitochondrial structure and function, its interaction with ATP synthase, and explored in vivo metabolism beyond the heart. RESULTS: Upon induction of dominant negative mitochondrial AKT1, CAMDAKT mice developed cardiac fibrosis accompanied by left ventricular hypertrophy and dysfunction. Cardiac mitochondrial oxidative phosphorylation efficiency and ATP content were reduced, mitochondrial cristae structure was lost, and ATP synthase structure was compromised. Conversely, CAMCAKT mice were protected against development of diabetic cardiomyopathy when challenged with a high calorie diet. Activation of mitochondrial AKT1 protected cardiac function and increased fatty acid uptake in myocardium. In addition, total energy expenditure was increased in CAMCAKT mice, accompanied by reduced adiposity and reduced development of fatty liver. CONCLUSION: CAMDAKT mice modeled the effects of impaired mitochondrial signaling which occurs in the diabetic myocardium. Disruption of this pathway is a key step in the development of cardiomyopathy. Activation of mitochondrial AKT1 in CAMCAKT had a protective role against diabetic cardiomyopathy as well as improved metabolism beyond the heart.

The cytokine IL-22 promotes pathogen colonization by suppressing related commensal bacteria.

Interleukin-22 (IL-22) is highly induced in response to infections with a variety of pathogens, and its main functions are considered to be tissue repair and host defense at mucosal surfaces. Here we showed that IL-22 has a unique role during infection in that its expression suppressed the intestinal microbiota and enhanced the colonization of a pathogen. IL-22 induced the expression of antimicrobial proteins, including lipocalin-2 and calprotectin, which sequester essential metal ions from microbes. Because Salmonella enterica ser. Typhimurium can overcome metal ion starvation mediated by lipocalin-2 and calprotectin via alternative pathways, IL-22 boosted its colonization of the inflamed intestine by suppressing commensal Enterobacteriaceae, which are susceptible to the antimicrobial proteins. Thus, IL-22 tipped the balance between pathogenic and commensal bacteria in favor of a pathogen. Taken together, IL-22 induction can be exploited by pathogens to suppress the growth of their closest competitors, thereby enhancing pathogen colonization of mucosal surfaces.

Coral and Seawater Metagenomes Reveal Key Microbial Functions to Coral Health and Ecosystem Functioning Shaped at Reef Scale.

The coral holobiont is comprised of a highly diverse microbial community that provides key services to corals such as protection against pathogens and nutrient cycling. The coral surface mucus layer (SML) microbiome is very sensitive to external changes, as it constitutes the direct interface between the coral host and the environment. Here, we investigate whether the bacterial taxonomic and functional profiles in the coral SML are shaped by the local reef zone and explore their role in coral health and ecosystem functioning. The analysis was conducted using metagenomes and metagenome-assembled genomes (MAGs) associated with the coral Pseudodiploria strigosa and the water column from two naturally distinct reef environments in Bermuda: inner patch reefs exposed to a fluctuating thermal regime and the more stable outer reefs. The microbial community structure in the coral SML varied according to the local environment, both at taxonomic and functional levels. The coral SML microbiome from inner reefs provides more gene functions that are involved in nutrient cycling (e.g., photosynthesis, phosphorus metabolism, sulfur assimilation) and those that are related to higher levels of microbial activity, competition, and stress response. In contrast, the coral SML microbiome from outer reefs contained genes indicative of a carbohydrate-rich mucus composition found in corals exposed to less stressful temperatures and showed high proportions of microbial gene functions that play a potential role in coral disease, such as degradation of lignin-derived compounds and sulfur oxidation. The fluctuating environment in the inner patch reefs of Bermuda could be driving a more beneficial coral SML microbiome, potentially increasing holobiont resilience to environmental changes and disease.

Genome-Wide B Cell, CD4+, and CD8+ T Cell Epitopes That Are Highly Conserved between Human and Animal Coronaviruses, Identified from SARS-CoV-2 as Targets for Preemptive Pan-Coronavirus Vaccines.

Over the last two decades, there have been three deadly human outbreaks of coronaviruses (CoVs) caused by SARS-CoV, MERS-CoV, and SARS-CoV-2, which has caused the current COVID-19 global pandemic. All three deadly CoVs originated from bats and transmitted to humans via various intermediate animal reservoirs. It remains highly possible that other global COVID pandemics will emerge in the coming years caused by yet another spillover of a bat-derived SARS-like coronavirus (SL-CoV) into humans. Determining the Ag and the human B cells, CD4+ and CD8+ T cell epitope landscapes that are conserved among human and animal coronaviruses should inform in the development of future pan-coronavirus vaccines. In the current study, using several immunoinformatics and sequence alignment approaches, we identified several human B cell and CD4+ and CD8+ T cell epitopes that are highly conserved in 1) greater than 81,000 SARS-CoV-2 genome sequences identified in 190 countries on six continents; 2) six circulating CoVs that caused previous human outbreaks of the common cold; 3) nine SL-CoVs isolated from bats; 4) nine SL-CoV isolated from pangolins; 5) three SL-CoVs isolated from civet cats; and 6) four MERS strains isolated from camels. Furthermore, the identified epitopes: 1) recalled B cells and CD4+ and CD8+ T cells from both COVID-19 patients and healthy individuals who were never exposed to SARS-CoV-2, and 2) induced strong B cell and T cell responses in humanized HLA-DR1/HLA-A*02:01 double-transgenic mice. The findings pave the way to develop a preemptive multiepitope pan-coronavirus vaccine to protect against past, current, and future outbreaks.

Organizing the bacterial annotation space with amino acid sequence embeddings.

BACKGROUND: Due to the ever-expanding gap between the number of proteins being discovered and their functional characterization, protein function inference remains a fundamental challenge in computational biology. Currently, known protein annotations are organized in human-curated ontologies, however, all possible protein functions may not be organized accurately. Meanwhile, recent advancements in natural language processing and machine learning have developed models which embed amino acid sequences as vectors in n-dimensional space. So far, these embeddings have primarily been used to classify protein sequences using manually constructed protein classification schemes. RESULTS: In this work, we describe the use of amino acid sequence embeddings as a systematic framework for studying protein ontologies. Using a sequence embedding, we show that the bacterial carbohydrate metabolism class within the SEED annotation system contains 48 clusters of embedded sequences despite this class containing 29 functional labels. Furthermore, by embedding Bacillus amino acid sequences with unknown functions, we show that these unknown sequences form clusters that are likely to have similar biological roles. CONCLUSIONS: This study demonstrates that amino acid sequence embeddings may be a powerful tool for developing more robust ontologies for annotating protein sequence data. In addition, embeddings may be beneficial for clustering protein sequences with unknown functions and selecting optimal candidate proteins to characterize experimentally.

Microcins mediate competition among Enterobacteriaceae in the inflamed gut.

The Enterobacteriaceae are a family of Gram-negative bacteria that include commensal organisms as well as primary and opportunistic pathogens that are among the leading causes of morbidity and mortality worldwide. Although Enterobacteriaceae often comprise less than 1% of a healthy intestine's microbiota, some of these organisms can bloom in the inflamed gut; expansion of enterobacteria is a hallmark of microbial imbalance known as dysbiosis. Microcins are small secreted proteins that possess antimicrobial activity in vitro, but whose role in vivo has been unclear. Here we demonstrate that microcins enable the probiotic bacterium Escherichia coli Nissle 1917 (EcN) to limit the expansion of competing Enterobacteriaceae (including pathogens and pathobionts) during intestinal inflammation. Microcin-producing EcN limits the growth of competitors in the inflamed intestine, including commensal E. coli, adherent-invasive E. coli and the related pathogen Salmonella enterica. Moreover, only therapeutic administration of the wild-type, microcin-producing EcN to mice previously infected with S. enterica substantially reduced intestinal colonization by the pathogen. Our work provides the first evidence that microcins mediate inter- and intraspecies competition among the Enterobacteriaceae in the inflamed gut. Moreover, we show that microcins can act as narrow-spectrum therapeutics to inhibit enteric pathogens and reduce enterobacterial blooms.

Analysis of Spounaviruses as a Case Study for the Overdue Reclassification of Tailed Phages.

Tailed bacteriophages are the most abundant and diverse viruses in the world, with genome sizes ranging from 10 kbp to over 500 kbp. Yet, due to historical reasons, all this diversity is confined to a single virus order-Caudovirales, composed of just four families: Myoviridae, Siphoviridae, Podoviridae, and the newly created Ackermannviridae family. In recent years, this morphology-based classification scheme has started to crumble under the constant flood of phage sequences, revealing that tailed phages are even more genetically diverse than once thought. This prompted us, the Bacterial and Archaeal Viruses Subcommittee of the International Committee on Taxonomy of Viruses (ICTV), to consider overall reorganization of phage taxonomy. In this study, we used a wide range of complementary methods-including comparative genomics, core genome analysis, and marker gene phylogenetics-to show that the group of Bacillus phage SPO1-related viruses previously classified into the Spounavirinae subfamily, is clearly distinct from other members of the family Myoviridae and its diversity deserves the rank of an autonomous family. Thus, we removed this group from the Myoviridae family and created the family Herelleviridae-a new taxon of the same rank. In the process of the taxon evaluation, we explored the feasibility of different demarcation criteria and critically evaluated the usefulness of our methods for phage classification. The convergence of results, drawing a consistent and comprehensive picture of a new family with associated subfamilies, regardless of method, demonstrates that the tools applied here are particularly useful in phage taxonomy. We are convinced that creation of this novel family is a crucial milestone toward much-needed reclassification in the Caudovirales order.

PhANNs, a fast and accurate tool and web server to classify phage structural proteins.

For any given bacteriophage genome or phage-derived sequences in metagenomic data sets, we are unable to assign a function to 50-90% of genes, or more. Structural protein-encoding genes constitute a large fraction of the average phage genome and are among the most divergent and difficult-to-identify genes using homology-based methods. To understand the functions encoded by phages, their contributions to their environments, and to help gauge their utility as potential phage therapy agents, we have developed a new approach to classify phage ORFs into ten major classes of structural proteins or into an "other" category. The resulting tool is named PhANNs (Phage Artificial Neural Networks). We built a database of 538,213 manually curated phage protein sequences that we split into eleven subsets (10 for cross-validation, one for testing) using a novel clustering method that ensures there are no homologous proteins between sets yet maintains the maximum sequence diversity for training. An Artificial Neural Network ensemble trained on features extracted from those sets reached a test F1-score of 0.875 and test accuracy of 86.2%. PhANNs can rapidly classify proteins into one of the ten structural classes or, if not predicted to fall in one of the ten classes, as "other," providing a new approach for functional annotation of phage proteins. PhANNs is open source and can be run from our web server or installed locally.

CRTAM Shapes the Gut Microbiota and Enhances the Severity of Infection.

Gut lymphocytes and the microbiota establish a reciprocal relationship that impacts the host immune response. Class I-restricted T cell-associated molecule (CRTAM) is a cell adhesion molecule expressed by intraepithelial T cells and is required for their retention in the gut. In this study, we show that CRTAM expression affects gut microbiota composition under homeostatic conditions. Moreover, Crtam-/- mice infected with the intestinal pathogen Salmonella exhibit reduced Th17 responses, lower levels of inflammation, and reduced Salmonella burden, which is accompanied by expansion of other microbial taxa. Thus, CRTAM enhances susceptibility to Salmonella, likely by promoting the inflammatory response that promotes the pathogen's growth. We also found that the gut microbiota from wild-type mice, but not from Crtam-/- mice, induces CRTAM expression and Th17 responses in ex-germ-free mice during Salmonella infection. Our study demonstrates a reciprocal relationship between CRTAM expression and the gut microbiota, which ultimately impacts the host response to enteric pathogens.

Genomic and ecological attributes of marine bacteriophages encoding bacterial virulence genes.

BACKGROUND: Bacteriophages encode genes that modify bacterial functions during infection. The acquisition of phage-encoded virulence genes is a major mechanism for the rise of bacterial pathogens. In coral reefs, high bacterial density and lysogeny has been proposed to exacerbate reef decline through the transfer of phage-encoded virulence genes. However, the functions and distribution of these genes in phage virions on the reef remain unknown. RESULTS: Here, over 28,000 assembled viral genomes from the free viral community in Atlantic and Pacific Ocean coral reefs were queried against a curated database of virulence genes. The diversity of virulence genes encoded in the viral genomes was tested for relationships with host taxonomy and bacterial density in the environment. These analyses showed that bacterial density predicted the profile of virulence genes encoded by phages. The Shannon diversity of virulence-encoding phages was negatively related with bacterial density, leading to dominance of fewer genes at high bacterial abundances. A statistical learning analysis showed that reefs with high microbial density were enriched in viruses encoding genes enabling bacterial recognition and invasion of metazoan epithelium. Over 60% of phages could not have their hosts identified due to limitations of host prediction tools; for those which hosts were identified, host taxonomy was not an indicator of the presence of virulence genes. CONCLUSIONS: This study described bacterial virulence factors encoded in the genomes of bacteriophages at the community level. The results showed that the increase in microbial densities that occurs during coral reef degradation is associated with a change in the genomic repertoire of bacteriophages, specifically in the diversity and distribution of bacterial virulence genes. This suggests that phages are implicated in the rise of pathogens in disturbed marine ecosystems.

PHANOTATE: a novel approach to gene identification in phage genomes.

MOTIVATION: Currently there are no tools specifically designed for annotating genes in phages. Several tools are available that have been adapted to run on phage genomes, but due to their underlying design, they are unable to capture the full complexity of phage genomes. Phages have adapted their genomes to be extremely compact, having adjacent genes that overlap and genes completely inside of other longer genes. This non-delineated genome structure makes it difficult for gene prediction using the currently available gene annotators. Here we present PHANOTATE, a novel method for gene calling specifically designed for phage genomes. Although the compact nature of genes in phages is a problem for current gene annotators, we exploit this property by treating a phage genome as a network of paths: where open reading frames are favorable, and overlaps and gaps are less favorable, but still possible. We represent this network of connections as a weighted graph, and use dynamic programing to find the optimal path. RESULTS: We compare PHANOTATE to other gene callers by annotating a set of 2133 complete phage genomes from GenBank, using PHANOTATE and the three most popular gene callers. We found that the four programs agree on 82% of the total predicted genes, with PHANOTATE predicting more genes than the other three. We searched for these extra genes in both GenBank's non-redundant protein database and all of the metagenomes in the sequence read archive, and found that they are present at levels that suggest that these are functional protein-coding genes. AVAILABILITY AND IMPLEMENTATION: https://github.com/deprekate/PHANOTATE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Siderophore-based immunization strategy to inhibit growth of enteric pathogens.

Infections with Gram-negative pathogens pose a serious threat to public health. This scenario is exacerbated by increases in antibiotic resistance and the limited availability of vaccines and therapeutic tools to combat these infections. Here, we report an immunization approach that targets siderophores, which are small molecules exported by enteric Gram-negative pathogens to acquire iron, an essential nutrient, in the host. Because siderophores are nonimmunogenic, we designed and synthesized conjugates of a native siderophore and the immunogenic carrier protein cholera toxin subunit B (CTB). Mice immunized with the CTB-siderophore conjugate developed anti-siderophore antibodies in the gut mucosa, and when mice were infected with the enteric pathogen Salmonella, they exhibited reduced intestinal colonization and reduced systemic dissemination of the pathogen. Moreover, analysis of the gut microbiota revealed that reduction of Salmonella colonization in the inflamed gut was accompanied by expansion of Lactobacillus spp., which are beneficial commensal organisms that thrive in similar locales as Enterobacteriaceae. Collectively, our results demonstrate that anti-siderophore antibodies inhibit Salmonella colonization. Because siderophore-mediated iron acquisition is a virulence trait shared by many bacterial and fungal pathogens, blocking microbial iron acquisition by siderophore-based immunization or other siderophore-targeted approaches may represent a novel strategy to prevent and ameliorate a broad range of infections.

Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer.

Much of the mechanism by which Wnt signaling drives proliferation during oncogenesis is attributed to its regulation of the cell cycle. Here, we show how Wnt/ß-catenin signaling directs another hallmark of tumorigenesis, namely Warburg metabolism. Using biochemical assays and fluorescence lifetime imaging microscopy (FLIM) to probe metabolism in vitro and in living tumors, we observe that interference with Wnt signaling in colon cancer cells reduces glycolytic metabolism and results in small, poorly perfused tumors. We identify pyruvate dehydrogenase kinase 1 (PDK1) as an important direct target within a larger gene program for metabolism. PDK1 inhibits pyruvate flux to mitochondrial respiration and a rescue of its expression in Wnt-inhibited cancer cells rescues glycolysis as well as vessel growth in the tumor microenvironment. Thus, we identify an important mechanism by which Wnt-driven Warburg metabolism directs the use of glucose for cancer cell proliferation and links it to vessel delivery of oxygen and nutrients.

PMAnalyzer: a new web interface for bacterial growth curve analysis.

SUMMARY: Bacterial growth curves are essential representations for characterizing bacteria metabolism within a variety of media compositions. Using high-throughput, spectrophotometers capable of processing tens of 96-well plates, quantitative phenotypic information can be easily integrated into the current data structures that describe a bacterial organism. The PMAnalyzer pipeline performs a growth curve analysis to parameterize the unique features occurring within microtiter wells containing specific growth media sources. We have expanded the pipeline capabilities and provide a user-friendly, online implementation of this automated pipeline. PMAnalyzer version 2.0 provides fast automatic growth curve parameter analysis, growth identification and high resolution figures of sample-replicate growth curves and several statistical analyses. AVAILABILITY AND IMPLEMENTATION: PMAnalyzer v2.0 can be found at https://edwards.sdsu.edu/pmanalyzer/ . Source code for the pipeline can be found on GitHub at https://github.com/dacuevas/PMAnalyzer . Source code for the online implementation can be found on GitHub at https://github.com/dacuevas/PMAnalyzerWeb . CONTACT: dcuevas08@gmail.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.