Bacterial DnaK reduces the activity of anti-cancer drugs cisplatin and 5FU.

BACKGROUND: Chemotherapy is a primary treatment for cancer, but its efficacy is often limited by cancer-associated bacteria (CAB) that impair tumor suppressor functions. Our previous research found that Mycoplasma fermentans DnaK, a chaperone protein, impairs p53 activities, which are essential for most anti-cancer chemotherapeutic responses. METHODS: To investigate the role of DnaK in chemotherapy, we treated cancer cell lines with M. fermentans DnaK and then with commonly used p53-dependent anti-cancer drugs (cisplatin and 5FU). We evaluated the cells' survival in the presence or absence of a DnaK-binding peptide (ARV-1502). We also validated our findings using primary tumor cells from a novel DnaK knock-in mouse model. To provide a broader context for the clinical significance of these findings, we investigated human primary cancer sequencing datasets from The Cancer Genome Atlas (TCGA). We identified F. nucleatum as a CAB carrying DnaK with an amino acid composition highly similar to M. fermentans DnaK. Therefore, we investigated the effect of F. nucleatum DnaK on the anti-cancer activity of cisplatin and 5FU. RESULTS: Our results show that both M. fermentans and F. nucleatum DnaKs reduce the effectiveness of cisplatin and 5FU. However, the use of ARV-1502 effectively restored the drugs' anti-cancer efficacy. CONCLUSIONS: Our findings offer a practical framework for designing and implementing novel personalized anti-cancer strategies by targeting specific bacterial DnaKs in patients with poor response to chemotherapy, underscoring the potential for microbiome-based personalized cancer therapies.

Direct sequencing of insect symbionts via nanopore adaptive sampling.

Insect symbionts can alter their host phenotype and their effects can range from beneficial to pathogenic. Moreover, many insects exhibit co-infections, making their study more challenging. Less than 1% of insect species have high-quality referenced genomes available and fewer still also have their symbionts sequenced. Two methods are commonly used to sequence symbionts: whole-genome sequencing to concomitantly capture the host and bacterial genomes, or isolation of the symbiont's genome before sequencing. These methods are limited when dealing with rare or poorly characterized symbionts. Long-read technology is an important tool to generate high-quality genomes as they can overcome high levels of heterozygosity, repeat content, and transposable elements that confound short-read methods. Oxford Nanopore (ONT) adaptive sampling allows a sequencing instrument to select or reject sequences in real time. We describe a method based on ONT adaptive sampling (subtractive) approach that readily permitted the sequencing of the complete genomes of mitochondria, Buchnera and its plasmids (pLeu, pTrp), and Wolbachia genomes in two aphid species, Aphis glycines and Pentalonia nigronervosa. Adaptive sampling is able to retrieve organelles such as mitochondria and symbionts that have high representation in their hosts such as Buchnera and Wolbachia, but is less successful at retrieving symbionts in low concentrations.

Comparative genomics of the niche-specific plant pathogen Streptomyces ipomoeae reveal novel genome content and organization.

IMPORTANCE: While most plant-pathogenic Streptomyces species cause scab disease on a variety of plant hosts, Streptomyces ipomoeae is the sole causative agent of soil rot disease of sweet potato and closely related plant species. Here, genome sequencing of virulent and avirulent S. ipomoeae strains coupled with comparative genomic analyses has identified genome content and organization features unique to this streptomycete plant pathogen. The results here will enable future research into the mechanisms used by S. ipomoeae to cause disease and to persist in its niche environment.

Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1.

Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with antitumor response to anti-programmed cell death protein-1 (PD-1) therapy, but inconsistencies exist between published microbial signatures associated with clinical outcomes. To resolve this, we evaluated a new melanoma cohort, along with four published datasets. Time-to-event analysis showed that baseline microbiota composition was optimally associated with clinical outcome at approximately 1 year after initiation of treatment. Meta-analysis and other bioinformatic analyses of the combined data show that bacteria associated with favorable response are confined within the Actinobacteria phylum and the Lachnospiraceae/Ruminococcaceae families of Firmicutes. Conversely, Gram-negative bacteria were associated with an inflammatory host intestinal gene signature, increased blood neutrophil-to-lymphocyte ratio, and unfavorable outcome. Two microbial signatures, enriched for Lachnospiraceae spp. and Streptococcaceae spp., were associated with favorable and unfavorable clinical response, respectively, and with distinct immune-related adverse effects. Despite between-cohort heterogeneity, optimized all-minus-one supervised learning algorithms trained on batch-corrected microbiome data consistently predicted outcomes to programmed cell death protein-1 therapy in all cohorts. Gut microbial communities (microbiotypes) with nonuniform geographical distribution were associated with favorable and unfavorable outcomes, contributing to discrepancies between cohorts. Our findings shed new light on the complex interaction between the gut microbiome and response to cancer immunotherapy, providing a roadmap for future studies.

Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response.

Gut bacteria modulate the response to immune checkpoint blockade (ICB) treatment in cancer, but the effect of diet and supplements on this interaction is not well studied. We assessed fecal microbiota profiles, dietary habits, and commercially available probiotic supplement use in melanoma patients and performed parallel preclinical studies. Higher dietary fiber was associated with significantly improved progression-free survival in 128 patients on ICB, with the most pronounced benefit observed in patients with sufficient dietary fiber intake and no probiotic use. Findings were recapitulated in preclinical models, which demonstrated impaired treatment response to anti­programmed cell death 1 (anti­PD-1)­based therapy in mice receiving a low-fiber diet or probiotics, with a lower frequency of interferon-γ­positive cytotoxic T cells in the tumor microenvironment. Together, these data have clinical implications for patients receiving ICB for cancer.

Neonatal exposure to a wild-derived microbiome protects mice against diet-induced obesity.

Obesity and its consequences are among the greatest challenges in healthcare. The gut microbiome is recognized as a key factor in the pathogenesis of obesity. Using a mouse model, we show here that a wild-derived microbiome protects against excessive weight gain, severe fatty liver disease and metabolic syndrome during a 10-week course of high-fat diet. This phenotype is transferable only during the first weeks of life. In adult mice, neither transfer nor severe disturbance of the wild-type microbiome modifies the metabolic response to a high-fat diet. The protective phenotype is associated with increased secretion of metabolic hormones and increased energy expenditure through activation of brown adipose tissue. Thus, we identify a microbiome that protects against weight gain and its negative consequences through metabolic programming in early life. Translation of these results to humans may identify early-life therapeutics that protect against obesity.

Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients.

Anti-programmed cell death protein 1 (PD-1) therapy provides long-term clinical benefits to patients with advanced melanoma. The composition of the gut microbiota correlates with anti-PD-1 efficacy in preclinical models and cancer patients. To investigate whether resistance to anti-PD-1 can be overcome by changing the gut microbiota, this clinical trial evaluated the safety and efficacy of responder-derived fecal microbiota transplantation (FMT) together with anti-PD-1 in patients with PD-1-refractory melanoma. This combination was well tolerated, provided clinical benefit in 6 of 15 patients, and induced rapid and durable microbiota perturbation. Responders exhibited increased abundance of taxa that were previously shown to be associated with response to anti-PD-1, increased CD8+ T cell activation, and decreased frequency of interleukin-8-expressing myeloid cells. Responders had distinct proteomic and metabolomic signatures, and transkingdom network analyses confirmed that the gut microbiome regulated these changes. Collectively, our findings show that FMT and anti-PD-1 changed the gut microbiome and reprogrammed the tumor microenvironment to overcome resistance to anti-PD-1 in a subset of PD-1 advanced melanoma.

Soybean aphid biotype 1 genome: Insights into the invasive biology and adaptive evolution of a major agricultural pest.

The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae) is a serious pest of the soybean plant, Glycine max, a major world-wide agricultural crop. We assembled a de novo genome sequence of Ap. glycines Biotype 1, from a culture established shortly after this species invaded North America. 20.4% of the Ap. glycines proteome is duplicated. These in-paralogs are enriched with Gene Ontology (GO) categories mostly related to apoptosis, a possible adaptation to plant chemistry and other environmental stressors. Approximately one-third of these genes show parallel duplication in other aphids. But Ap. gossypii, its closest related species, has the lowest number of these duplicated genes. An Illumina GoldenGate assay of 2380 SNPs was used to determine the world-wide population structure of Ap. Glycines. China and South Korean aphids are the closest to those in North America. China is the likely origin of other Asian aphid populations. The most distantly related aphids to those in North America are from Australia. The diversity of Ap. glycines in North America has decreased over time since its arrival. The genetic diversity of Ap. glycines North American population sampled shortly after its first detection in 2001 up to 2012 does not appear to correlate with geography. However, aphids collected on soybean Rag experimental varieties in Minnesota (MN), Iowa (IA), and Wisconsin (WI), closer to high density Rhamnus cathartica stands, appear to have higher capacity to colonize resistant soybean plants than aphids sampled in Ohio (OH), North Dakota (ND), and South Dakota (SD). Samples from the former states have SNP alleles with high FST values and frequencies, that overlap with genes involved in iron metabolism, a crucial metabolic pathway that may be affected by the Rag-associated soybean plant response. The Ap. glycines Biotype 1 genome will provide needed information for future analyses of mechanisms of aphid virulence and pesticide resistance as well as facilitate comparative analyses between aphids with differing natural history and host plant range.

Microbiome as an Immunological Modifier.

Humans are living ecosystems composed of human cells and microbes. The microbiome is the collection of microbes (microbiota) and their genes. Recent breakthroughs in the high-throughput sequencing technologies have made it possible for us to understand the composition of the human microbiome. Launched by the National Institutes of Health in USA, the human microbiome project indicated that our bodies harbor a wide array of microbes, specific to each body site with interpersonal and intrapersonal variabilities. Numerous studies have indicated that several factors influence the development of the microbiome including genetics, diet, use of antibiotics, and lifestyle, among others. The microbiome and its mediators are in a continuous cross talk with the host immune system; hence, any imbalance on one side is reflected on the other. Dysbiosis (microbiota imbalance) was shown in many diseases and pathological conditions such as inflammatory bowel disease, celiac disease, multiple sclerosis, rheumatoid arthritis, asthma, diabetes, and cancer. The microbial composition mirrors inflammation variations in certain disease conditions, within various stages of the same disease; hence, it has the potential to be used as a biomarker.

Laboratory mice born to wild mice have natural microbiota and model human immune responses.

Laboratory mouse studies are paramount for understanding basic biological phenomena but also have limitations. These include conflicting results caused by divergent microbiota and limited translational research value. To address both shortcomings, we transferred C57BL/6 embryos into wild mice, creating "wildlings." These mice have a natural microbiota and pathogens at all body sites and the tractable genetics of C57BL/6 mice. The bacterial microbiome, mycobiome, and virome of wildlings affect the immune landscape of multiple organs. Their gut microbiota outcompete laboratory microbiota and demonstrate resilience to environmental challenges. Wildlings, but not conventional laboratory mice, phenocopied human immune responses in two preclinical studies. A combined natural microbiota- and pathogen-based model may enhance the reproducibility of biomedical studies and increase the bench-to-bedside safety and success of immunological studies.

Description of soybean aphid (Aphis glycines Matsumura) mitochondrial genome and comparative mitogenomics of Aphididae (Hemiptera: Sternorrhyncha).

The complete mitochondrial genome of the soybean aphid (Aphis glycines Matsumura), a major agricultural pest in the world, is described for the first time, which consists of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, as well as a large repeat region between tRNA-Glu and tRNA-Phe, and an AT-rich control region. The 17,954 bp mtgenome is the largest reported from the family Aphididae, and its gene order follows the ancestral insect mtgenome except for the repeat region, which contains a 195 bp unit repeated 11.9 times, representing the highest reported repeats among the known aphid mtgenomes to date. A new molecular phylogeny of Aphidae is reconstructed based on all available aphid mtgenomes, and it is shown that the mtgenome data can robustly resolve relationships at the subfamily level, but do not have sufficient phylogenetic information to resolve deep relationships. A phylogeny-based comparative analysis of mtgenomes has been performed to investigate the evolution of the repeat region between tRNA-Glu and tRNA-Phe. So far, among aphids, 13 species are known to have this repeat region of variable lengths, and a phylogenetic analysis of the repeat region shows that a large proportion of the sequences are conserved across the phylogeny, suggesting that the repeat region evolved in the most recent common ancestor of Aphidinae and Eriosomatinae, and that it has gone through numerous episodes of lineage-specific losses and expansions. Combined together, this study provides novel insights into how the repeat regions have evolved within aphids.

Machine learning for phenotyping opioid overdose events.

OBJECTIVE: To develop machine learning models for classifying the severity of opioid overdose events from clinical data. MATERIALS AND METHODS: Opioid overdoses were identified by diagnoses codes from the Marshfield Clinic population and assigned a severity score via chart review to form a gold standard set of labels. Three primary feature sets were constructed from disparate data sources surrounding each event and used to train machine learning models for phenotyping. RESULTS: Random forest and penalized logistic regression models gave the best performance with cross-validated mean areas under the ROC curves (AUCs) for all severity classes of 0.893 and 0.882 respectively. Features derived from a common data model outperformed features collected from disparate data sources for the same cohort of patients (AUCs 0.893 versus 0.837, p value = 0.002). The addition of features extracted from free text to machine learning models also increased AUCs from 0.827 to 0.893 (p value < 0.0001). Key word features extracted using natural language processing (NLP) such as 'Narcan' and 'Endotracheal Tube' are important for classifying overdose event severity. CONCLUSION: Random forest models using features derived from a common data model and free text can be effective for classifying opioid overdose events.

An Interleukin-23-Interleukin-22 Axis Regulates Intestinal Microbial Homeostasis to Protect from Diet-Induced Atherosclerosis.

Although commensal flora is involved in the regulation of immunity, the interplay between cytokine signaling and microbiota in atherosclerosis remains unknown. We found that interleukin (IL)-23 and its downstream target IL-22 restricted atherosclerosis by repressing pro-atherogenic microbiota. Inactivation of IL-23-IL-22 signaling led to deterioration of the intestinal barrier, dysbiosis, and expansion of pathogenic bacteria with distinct biosynthetic and metabolic properties, causing systemic increase in pro-atherogenic metabolites such as lipopolysaccharide (LPS) and trimethylamine N-oxide (TMAO). Augmented disease in the absence of the IL-23-IL-22 pathway was mediated in part by pro-atherogenic osteopontin, controlled by microbial metabolites. Microbiota transfer from IL-23-deficient mice accelerated atherosclerosis, whereas microbial depletion or IL-22 supplementation reduced inflammation and ameliorated disease. Our work uncovers the IL-23-IL-22 signaling as a regulator of atherosclerosis that restrains expansion of pro-atherogenic microbiota and argues for informed use of cytokine blockers to avoid cardiovascular side effects driven by microbiota and inflammation.

Using Machine Learning Algorithms to Predict Risk for Development of Calciphylaxis in Patients with Chronic Kidney Disease.

Calciphylaxis is a disorder that results in necrotic cutaneous lesions with a high rate of mortality. Due to its rarity and complexity, the risk factors for and the disease mechanism of calciphylaxis are not fully understood. This work focuses on the use of machine learning to both predict disease risk and model the contributing factors learned from an electronic health record data set. We present the results of four modeling approaches on several subpopulations of patients with chronic kidney disease (CKD). We find that modeling calciphylaxis risk with random forests learned from binary feature data produces strong models, and in the case of predicting calciphylaxis development among stage 4 CKD patients, we achieve an AUC-ROC of 0.8718. This ability to successfully predict calciphylaxis may provide an excellent opportunity for clinical translation of the predictive models presented in this paper.

The Antimicrobial Peptide CRAMP Is Essential for Colon Homeostasis by Maintaining Microbiota Balance.

Commensal bacteria are critical for physiological functions in the gut, and dysbiosis in the gut may cause diseases. In this article, we report that mice deficient in cathelin-related antimicrobial peptide (CRAMP) were defective in the development of colon mucosa and highly sensitive to dextran sulfate sodium (DSS)-elicited colitis, as well as azoxymethane-mediated carcinogenesis. Pretreatment of CRAMP-/- mice with antibiotics markedly reduced the severity of DSS-induced colitis, suggesting CRAMP as a limiting factor on dysbiosis in the colon. This was supported by observations that wild-type (WT) mice cohoused with CRAMP-/- mice became highly sensitive to DSS-induced colitis, and the composition of fecal microbiota was skewed by CRAMP deficiency. In particular, several bacterial species that are typically found in oral microbiota, such as Mogibacterium neglectum, Desulfovibrio piger, and Desulfomicrobium orale, were increased in feces of CRAMP-/- mice and were transferred to WT mice during cohousing. When littermates of CRAMP+/- parents were examined, the composition of the fecal microbiota of WT pups and heterozygous parents was similar. In contrast, although the difference in fecal microbiota between CRAMP-/- and WT pups was small early on after weaning and single mouse housing, there was an increasing divergence with prolonged single housing. These results indicate that CRAMP is critical in maintaining colon microbiota balance and supports mucosal homeostasis, anti-inflammatory responses, and protection from carcinogenesis.

Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure.

BACKGROUND: The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. OBJECTIVE: The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs. METHODS: We analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural language processing, and machine learning. This was combined with an Elasticsearch No-SQL distributed database to explore and visualize ADEs. RESULTS: The accuracy, precision, recall, and area under receiver operating characteristic of the system were 92.7%, 93.6%, 93.0%, and 0.905, respectively, and showed better results in comparison with traditional approaches in the literature. This work not only detected and classified ADE sentences from big data biomedical literature but also scientifically visualized ADE interactions. CONCLUSIONS: To the best of our knowledge, this work is the first to investigate a big data machine learning strategy for ADE discovery on massive datasets downloaded from PubMed Central and social media. This contribution illustrates possible capacities in big data biomedical text analysis using advanced computational methods with real-time update from new data published on a daily basis.

Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance.

Laboratory mice, while paramount for understanding basic biological phenomena, are limited in modeling complex diseases of humans and other free-living mammals. Because the microbiome is a major factor in mammalian physiology, we aimed to identify a naturally evolved reference microbiome to better recapitulate physiological phenomena relevant in the natural world outside the laboratory. Among 21 distinct mouse populations worldwide, we identified a closely related wild relative to standard laboratory mouse strains. Its bacterial gut microbiome differed significantly from its laboratory mouse counterpart and was transferred to and maintained in laboratory mice over several generations. Laboratory mice reconstituted with natural microbiota exhibited reduced inflammation and increased survival following influenza virus infection and improved resistance against mutagen/inflammation-induced colorectal tumorigenesis. By demonstrating the host fitness-promoting traits of natural microbiota, our findings should enable the discovery of protective mechanisms relevant in the natural world and improve the modeling of complex diseases of free-living mammals. VIDEO ABSTRACT.

Correction: Transcriptional Orchestration of the Global Cellular Response of a Model Pennate Diatom to Diel Light Cycling under Iron Limitation.

[This corrects the article DOI: 10.1371/journal.pgen.1006490.].

The Baltic Sea Virome: Diversity and Transcriptional Activity of DNA and RNA Viruses.

Metagenomic and metatranscriptomic data were generated from size-fractionated samples from 11 sites within the Baltic Sea and adjacent marine waters of Kattegat and freshwater Lake Torneträsk in order to investigate the diversity, distribution, and transcriptional activity of virioplankton. Such a transect, spanning a salinity gradient from freshwater to the open sea, facilitated a broad genome-enabled investigation of natural as well as impacted aspects of Baltic Sea viral communities. Taxonomic signatures representative of phages within the widely distributed order Caudovirales were identified with enrichments in lesser-known families such as Podoviridae and Siphoviridae. The distribution of phage reported to infect diverse and ubiquitous heterotrophic bacteria (SAR11 clades) and cyanobacteria (Synechococcus sp.) displayed population-level shifts in diversity. Samples from higher-salinity conditions (>14 practical salinity units [PSU]) had increased abundances of viruses for picoeukaryotes, i.e., Ostreococcus. These data, combined with host diversity estimates, suggest viral modulation of diversity on the whole-community scale, as well as in specific prokaryotic and eukaryotic lineages. RNA libraries revealed single-stranded DNA (ssDNA) and RNA viral populations throughout the Baltic Sea, with ssDNA phage highly represented in Lake Torneträsk. Further, our data suggest relatively high transcriptional activity of fish viruses within diverse families known to have broad host ranges, such as Nodoviridae (RNA), Iridoviridae (DNA), and predicted zoonotic viruses that can cause ecological and economic damage as well as impact human health. IMPORTANCE Inferred virus-host relationships, community structures of ubiquitous ecologically relevant groups, and identification of transcriptionally active populations have been achieved with our Baltic Sea study. Further, these data, highlighting the transcriptional activity of viruses, represent one of the more powerful uses of omics concerning ecosystem health. The use of omics-related data to assess ecosystem health holds great promise for rapid and relatively inexpensive determination of perturbations and risk, explicitly with regard to viral assemblages, as no single marker gene is suitable for widespread taxonomic coverage.

Microbes and Cancer.

Commensal microorganisms (the microbiota) live on all the surface barriers of our body and are particularly abundant and diverse in the distal gut. The microbiota and its larger host represent a metaorganism in which the cross talk between microbes and host cells is necessary for health, survival, and regulation of physiological functions locally, at the barrier level, and systemically. The ancestral molecular and cellular mechanisms stemming from the earliest interactions between prokaryotes and eukaryotes have evolved to mediate microbe-dependent host physiology and tissue homeostasis, including innate and adaptive resistance to infections and tissue repair. Mostly because of its effects on metabolism, cellular proliferation, inflammation, and immunity, the microbiota regulates cancer at the level of predisposing conditions, initiation, genetic instability, susceptibility to host immune response, progression, comorbidity, and response to therapy. Here, we review the mechanisms underlying the interaction of the microbiota with cancer and the evidence suggesting that the microbiota could be targeted to improve therapy while attenuating adverse reactions.