The diversity of the microbiome impacts chronic lymphocytic leukemia development in mice and humans.

The gut microbiota play a critical role in maintaining a healthy human body and their dysregulation is associated with various diseases. In this study, we investigated the influence of the gut microbiome diversity on chronic lymphocytic leukemia (CLL) development. Stool sample analysis of 59 CLL patients revealed individual and heterogeneous microbiome compositions, but allowed for grouping of patients according to their microbiome diversity. Interestingly, CLL patients with a lower microbiome diversity and an enrichment of bacteria linked to poor health suffered from a more advanced or aggressive form of CLL. In the Eµ-TCL1 mouse model of CLL, we observed a faster course of disease when mice were housed in high hygiene conditions. Shotgun DNA sequencing of fecal samples showed that this was associated with a lower microbiome diversity which was dominated by Mucispirillum and Parabacteroides genera in comparison to mice kept under lower hygiene conditions. In conclusion, we applied taxonomic microbiome analyses to demonstrate a link between the gut microbiome diversity and the clinical course of CLL in humans, as well as the development of CLL in mice. Our novel data serve as a basis for further investigations to decipher the pathological and mechanistic role of intestinal microbiota in CLL development.

Functional and evolutionary significance of unknown genes from uncultivated taxa.

Many of the Earth's microbes remain uncultured and understudied, limiting our understanding of the functional and evolutionary aspects of their genetic material, which remain largely overlooked in most metagenomic studies1. Here we analysed 149,842 environmental genomes from multiple habitats2-6 and compiled a curated catalogue of 404,085 functionally and evolutionarily significant novel (FESNov) gene families exclusive to uncultivated prokaryotic taxa. All FESNov families span multiple species, exhibit strong signals of purifying selection and qualify as new orthologous groups, thus nearly tripling the number of bacterial and archaeal gene families described to date. The FESNov catalogue is enriched in clade-specific traits, including 1,034 novel families that can distinguish entire uncultivated phyla, classes and orders, probably representing synapomorphies that facilitated their evolutionary divergence. Using genomic context analysis and structural alignments we predicted functional associations for 32.4% of FESNov families, including 4,349 high-confidence associations with important biological processes. These predictions provide a valuable hypothesis-driven framework that we used for experimental validatation of a new gene family involved in cell motility and a novel set of antimicrobial peptides. We also demonstrate that the relative abundance profiles of novel families can discriminate between environments and clinical conditions, leading to the discovery of potentially new biomarkers associated with colorectal cancer. We expect this work to enhance future metagenomics studies and expand our knowledge of the genetic repertory of uncultivated organisms.

Sphingolipids Are Depleted in Alcohol-Related Liver Fibrosis.

BACKGROUND & AIMS: Alcohol disturbs hepatic lipid synthesis and transport, but the role of lipid dysfunction in alcohol-related liver disease (ALD) is unclear. In this biopsy-controlled, prospective, observational study, we characterized the liver and plasma lipidomes in patients with early ALD. METHODS: We performed mass spectrometry-based lipidomics of paired liver and plasma samples from 315 patients with ALD and of plasma from 51 matched healthy controls. We associated lipid levels with histologic fibrosis, inflammation, and steatosis with correction for multiple testing and adjustment for confounders. We further investigated sphingolipid regulation by means of quantitative real-time polymerase chain reaction sequencing of microRNA, prediction of liver-related events, and tested causality with Mendelian randomization. RESULTS: We detected 198 lipids in the liver and 236 lipids in the circulation from 18 lipid classes. Most sphingolipids (sphingomyelins and ceramides) and phosphocholines were co-down-regulated in both liver and plasma, where lower abundance correlated with higher fibrosis stage. Sphingomyelins showed the most pronounced negative correlation to fibrosis, mirrored by negative correlations in both liver and plasma with hepatic inflammation. Reduced sphingomyelins predicted future liver-related events. This seemed to be characteristic of "pure ALD," as sphingomyelin levels were higher in patients with concomitant metabolic syndrome and ALD/nonalcoholic fatty liver disease overlap. Mendelian randomization in FinnGen and UK Biobanks indicated ALD as the cause of low sphingomyelins, and alcohol use disorder did not correlate with genetic susceptibility to low sphingomyelin levels. CONCLUSIONS: Alcohol-related liver fibrosis is characterized by selective and progressive lipid depletion in liver and blood, particularly sphingomyelins, which also associates with progression to liver-related events.

Dissecting the intracellular pancreatic tumor microbiome at single-cell level.

Microorganisms play a role in the progression of various cancers. In this issue of Cancer Cell, Ghaddar et al. traced bacteria in pancreatic tumors at single-cell resolution and associated their intracellular presence with cell-type-specific transcriptional shifts, with links to clinical prognosis.

Metagenomic Identification of Microbial Signatures Predicting Pancreatic Cancer From a Multinational Study.

BACKGROUND & AIMS: To identify gut and oral metagenomic signatures that accurately predict pancreatic ductal carcinoma (PDAC) and to validate these signatures in independent cohorts. METHODS: We conducted a multinational study and performed shotgun metagenomic analysis of fecal and salivary samples collected from patients with treatment-naïve PDAC and non-PDAC controls in Japan, Spain, and Germany. Taxonomic and functional profiles of the microbiomes were characterized, and metagenomic classifiers to predict PDAC were constructed and validated in external datasets. RESULTS: Comparative metagenomics revealed dysbiosis of both the gut and oral microbiomes and identified 30 gut and 18 oral species significantly associated with PDAC in the Japanese cohort. These microbial signatures achieved high area under the curve values of 0.78 to 0.82. The prediction model trained on the Japanese gut microbiome also had high predictive ability in Spanish and German cohorts, with respective area under the curve values of 0.74 and 0.83, validating its high confidence and versatility for PDAC prediction. Significant enrichments of Streptococcus and Veillonella spp and a depletion of Faecalibacterium prausnitzii were common gut signatures for PDAC in all the 3 cohorts. Prospective follow-up data revealed that patients with certain gut and oral microbial species were at higher risk of PDAC-related mortality. Finally, 58 bacteriophages that could infect microbial species consistently enriched in patients with PDAC across the 3 countries were identified. CONCLUSIONS: Metagenomics targeting the gut and oral microbiomes can provide a powerful source of biomarkers for identifying individuals with PDAC and their prognoses. The identification of shared gut microbial signatures for PDAC in Asian and European cohorts indicates the presence of robust and global gut microbial biomarkers.

A faecal microbiota signature with high specificity for pancreatic cancer.

BACKGROUND: Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression. OBJECTIVE: To explore the faecal and salivary microbiota as potential diagnostic biomarkers. METHODS: We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase. RESULTS: Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation. CONCLUSION: Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Recurrent Frameshift Neoantigen Vaccine Elicits Protective Immunity With Reduced Tumor Burden and Improved Overall Survival in a Lynch Syndrome Mouse Model.

BACKGROUND & AIMS: DNA mismatch repair deficiency drives microsatellite instability (MSI). Cells with MSI accumulate numerous frameshift mutations. Frameshift mutations affecting cancer-related genes may promote tumorigenesis and, therefore, are shared among independently arising MSI tumors. Consequently, such recurrent frameshift mutations can give rise to shared immunogenic frameshift peptides (FSPs) that represent ideal candidates for a vaccine against MSI cancer. Pathogenic germline variants of mismatch repair genes cause Lynch syndrome (LS), a hereditary cancer syndrome affecting approximately 20-25 million individuals worldwide. Individuals with LS are at high risk of developing MSI cancer. Previously, we demonstrated safety and immunogenicity of an FSP-based vaccine in a phase I/IIa clinical trial in patients with a history of MSI colorectal cancer. However, the cancer-preventive effect of FSP vaccination in the scenario of LS has not yet been demonstrated. METHODS: A genome-wide database of 488,235 mouse coding mononucleotide repeats was established, from which a set of candidates was selected based on repeat length, gene expression, and mutation frequency. In silico prediction, in vivo immunogenicity testing, and epitope mapping was used to identify candidates for FSP vaccination. RESULTS: We identified 4 shared FSP neoantigens (Nacad [FSP-1], Maz [FSP-1], Senp6 [FSP-1], Xirp1 [FSP-1]) that induced CD4/CD8 T cell responses in naïve C57BL/6 mice. Using VCMsh2 mice, which have a conditional knockout of Msh2 in the intestinal tract and develop intestinal cancer, we showed vaccination with a combination of only 4 FSPs significantly increased FSP-specific adaptive immunity, reduced intestinal tumor burden, and prolonged overall survival. Combination of FSP vaccination with daily naproxen treatment potentiated immune response, delayed tumor growth, and prolonged survival even more effectively than FSP vaccination alone. CONCLUSIONS: Our preclinical findings support a clinical strategy of recurrent FSP neoantigen vaccination for LS cancer immunoprevention.

Microbiome meta-analysis and cross-disease comparison enabled by the SIAMCAT machine learning toolbox.

The human microbiome is increasingly mined for diagnostic and therapeutic biomarkers using machine learning (ML). However, metagenomics-specific software is scarce, and overoptimistic evaluation and limited cross-study generalization are prevailing issues. To address these, we developed SIAMCAT, a versatile R toolbox for ML-based comparative metagenomics. We demonstrate its capabilities in a meta-analysis of fecal metagenomic studies (10,803 samples). When naively transferred across studies, ML models lost accuracy and disease specificity, which could however be resolved by a novel training set augmentation strategy. This reveals some biomarkers to be disease-specific, with others shared across multiple conditions. SIAMCAT is freely available from siamcat.embl.de .

OGEE v3: Online GEne Essentiality database with increased coverage of organisms and human cell lines.

OGEE is an Online GEne Essentiality database. Gene essentiality is not a static and binary property, rather a context-dependent and evolvable property in all forms of life. In OGEE we collect not only experimentally tested essential and non-essential genes, but also associated gene properties that contributes to gene essentiality. We tagged conditionally essential genes that show variable essentiality statuses across datasets to highlight complex interplays between gene functions and environmental/experimental perturbations. OGEE v3 contains gene essentiality datasets for 91 species; almost doubled from 48 species in previous version. To accommodate recent advances on human cancer essential genes (as known as tumor dependency genes) that could serve as targets for cancer treatment and/or drug development, we expanded the collection of human essential genes from 16 cell lines in previous to 581. These human cancer cell lines were tested with high-throughput experiments such as CRISPR-Cas9 and RNAi; in total, 150 of which were tested by both techniques. We also included factors known to contribute to gene essentiality for these cell lines, such as genomic mutation, methylation and gene expression, along with extensive graphical visualizations for ease of understanding of these factors. OGEE v3 can be accessible freely at https://v3.ogee.info.

Glycogen accumulation, central carbon metabolism, and aging of hematopoietic stem and progenitor cells.

Inspired by recent proteomic data demonstrating the upregulation of carbon and glycogen metabolism in aging human hematopoietic stem and progenitor cells (HPCs, CD34+ cells), this report addresses whether this is caused by elevated glycolysis of the HPCs on a per cell basis, or by a subpopulation that has become more glycolytic. The average glycogen content in individual CD34+ cells from older subjects (> 50 years) was 3.5 times higher and more heterogeneous compared to younger subjects (< 35 years). Representative glycolytic enzyme activities in HPCs confirmed a significant increase in glycolysis in older subjects. The HPCs from older subjects can be fractionated into three distinct subsets with high, intermediate, and low glucose uptake (GU) capacity, while the subset with a high GU capacity could scarcely be detected in younger subjects. Thus, we conclude that upregulated glycolysis in aging HPCs is caused by the expansion of a more glycolytic HPC subset. Since single-cell RNA analysis has also demonstrated that this subpopulation is linked to myeloid differentiation and increased proliferation, isolation and mechanistic characterization of this subpopulation can be utilized to elucidate specific targets for therapeutic interventions to restore the lineage balance of aging HPCs.

(Phospho)proteomic Profiling of Microsatellite Unstable CRC Cells Reveals Alterations in Nuclear Signaling and Cholesterol Metabolism Caused by Frameshift Mutation of NMD Regulator UPF3A.

DNA mismatch repair-deficient colorectal cancers (CRCs) accumulate numerous frameshift mutations at repetitive sequences recognized as microsatellite instability (MSI). When coding mononucleotide repeats (cMNRs) are affected, tumors accumulate frameshift mutations and premature termination codons (PTC) potentially leading to truncated proteins. Nonsense-mediated RNA decay (NMD) can degrade PTC-containing transcripts and protect from such faulty proteins. As it also regulates normal transcripts and cellular physiology, we tested whether NMD genes themselves are targets of MSI frameshift mutations. A high frequency of cMNR frameshift mutations in the UPF3A gene was found in MSI CRC cell lines (67.7%), MSI colorectal adenomas (55%) and carcinomas (63%). In normal colonic crypts, UPF3A expression was restricted to single chromogranin A-positive cells. SILAC-based proteomic analysis of KM12 CRC cells revealed UPF3A-dependent down-regulation of several enzymes involved in cholesterol biosynthesis. Furthermore, reconstituted UPF3A expression caused alterations of 85 phosphosites in 52 phosphoproteins. Most of them (38/52, 73%) reside in nuclear phosphoproteins involved in regulation of gene expression and RNA splicing. Since UPF3A mutations can modulate the (phospho)proteomic signature and expression of enzymes involved in cholesterol metabolism in CRC cells, UPF3A may influence other processes than NMD and loss of UPF3A expression might provide a growth advantage to MSI CRC cells.

Quantitative Proteome Landscape of the NCI-60 Cancer Cell Lines.

Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, ß-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.

Author Correction: Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer.

Association studies have linked microbiome alterations with many human diseases. However, they have not always reported consistent results, thereby necessitating cross-study comparisons. Here, a meta-analysis of eight geographically and technically diverse fecal shotgun metagenomic studies of colorectal cancer (CRC, n = 768), which was controlled for several confounders, identified a core set of 29 species significantly enriched in CRC metagenomes (false discovery rate (FDR) < 1 × 10-5). CRC signatures derived from single studies maintained their accuracy in other studies. By training on multiple studies, we improved detection accuracy and disease specificity for CRC. Functional analysis of CRC metagenomes revealed enriched protein and mucin catabolism genes and depleted carbohydrate degradation genes. Moreover, we inferred elevated production of secondary bile acids from CRC metagenomes, suggesting a metabolic link between cancer-associated gut microbes and a fat- and meat-rich diet. Through extensive validations, this meta-analysis firmly establishes globally generalizable, predictive taxonomic and functional microbiome CRC signatures as a basis for future diagnostics.

Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation.

Several studies have investigated links between the gut microbiome and colorectal cancer (CRC), but questions remain about the replicability of biomarkers across cohorts and populations. We performed a meta-analysis of five publicly available datasets and two new cohorts and validated the findings on two additional cohorts, considering in total 969 fecal metagenomes. Unlike microbiome shifts associated with gastrointestinal syndromes, the gut microbiome in CRC showed reproducibly higher richness than controls (P < 0.01), partially due to expansions of species typically derived from the oral cavity. Meta-analysis of the microbiome functional potential identified gluconeogenesis and the putrefaction and fermentation pathways as being associated with CRC, whereas the stachyose and starch degradation pathways were associated with controls. Predictive microbiome signatures for CRC trained on multiple datasets showed consistently high accuracy in datasets not considered for model training and independent validation cohorts (average area under the curve, 0.84). Pooled analysis of raw metagenomes showed that the choline trimethylamine-lyase gene was overabundant in CRC (P = 0.001), identifying a relationship between microbiome choline metabolism and CRC. The combined analysis of heterogeneous CRC cohorts thus identified reproducible microbiome biomarkers and accurate disease-predictive models that can form the basis for clinical prognostic tests and hypothesis-driven mechanistic studies.

Disentangling Genetic and Environmental Effects on the Proteotypes of Individuals.

Proteotypes, like genotypes, have been found to vary between individuals in several studies, but consistent molecular functional traits across studies remain to be quantified. In a meta-analysis of 11 proteomics datasets from humans and mice, we use co-variation of proteins in known functional modules across datasets and individuals to obtain a consensus landscape of proteotype variation. We find that individuals differ considerably in both protein complex abundances and stoichiometry. We disentangle genetic and environmental factors impacting these metrics, with genetic sex and specific diets together explaining 13.5% and 11.6% of the observed variation of complex abundance and stoichiometry, respectively. Sex-specific differences, for example, include various proteins and complexes, where the respective genes are not located on sex-specific chromosomes. Diet-specific differences, added to the individual genetic backgrounds, might become a starting point for personalized proteotype modulation toward desired features.

Extensive transmission of microbes along the gastrointestinal tract.

The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease.

Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline.

Diminishing potential to replace damaged tissues is a hallmark for ageing of somatic stem cells, but the mechanisms remain elusive. Here, we present proteome-wide atlases of age-associated alterations in human haematopoietic stem and progenitor cells (HPCs) and five other cell populations that constitute the bone marrow niche. For each, the abundance of a large fraction of the ~12,000 proteins identified is assessed in 59 human subjects from different ages. As the HPCs become older, pathways in central carbon metabolism exhibit features reminiscent of the Warburg effect, where glycolytic intermediates are rerouted towards anabolism. Simultaneously, altered abundance of early regulators of HPC differentiation reveals a reduced functionality and a bias towards myeloid differentiation. Ageing causes alterations in the bone marrow niche too, and diminishes the functionality of the pathways involved in HPC homing. The data represent a valuable resource for further analyses, and for validation of knowledge gained from animal models.

Copy number variation analysis and targeted NGS in 77 families with suspected Lynch syndrome reveals novel potential causative genes.

In many families with suspected Lynch syndrome (LS), no germline mutation in the causative mismatch repair (MMR) genes is detected during routine diagnostics. To identify novel causative genes for LS, the present study investigated 77 unrelated, mutation-negative patients with clinically suspected LS and a loss of MSH2 in tumor tissue. An analysis for genomic copy number variants (CNV) was performed, with subsequent next generation sequencing (NGS) of selected candidate genes in a subgroup of the cohort. Genomic DNA was genotyped using Illumina's HumanOmniExpress Bead Array. After quality control and filtering, 25 deletions and 16 duplications encompassing 73 genes were identified in 28 patients. No recurrent CNV was detected, and none of the CNVs affected the regulatory regions of MSH2. A total of 49 candidate genes from genomic regions implicated by the present CNV analysis and 30 known or assumed risk genes for colorectal cancer (CRC) were then sequenced in a subset of 38 patients using a customized NGS gene panel and Sanger sequencing. Single nucleotide variants were identified in 14 candidate genes from the CNV analysis. The most promising of these candidate genes were: (i) PRKCA, PRKDC, and MCM4, as a functional relation to MSH2 is predicted by network analysis, and (ii) CSMD1, as this is commonly mutated in CRC. Furthermore, six patients harbored POLE variants outside the exonuclease domain, suggesting that these might be implicated in hereditary CRC. Analyses in larger cohorts of suspected LS patients recruited via international collaborations are warranted to verify the present findings.

[Microbial Biomarkers for Early Cancer Detection]. / Mikrobielle Biomarker zur Krebsfrüherkennung.

The human microbiome - the vast amount of microbes that colonize our body - play an important role in maintaining our health. Changes in microbiome composition have been linked to multiple diseases including cancer. Although mechanisms and causalities of these associations still have to be uncovered, microbiome alterations across various stages of disease can be utilized for novel diagnostic and prognostic tests. Research on biomarkers extracted from the gut microbiome has in particular focused on colorectal cancer, where clinical use is already on the horizon. For example, multiple microbial taxonomic markers such as Fusobacterium nucleatum and other oral pathogens have been identified in human feces with potential for non-invasive diagnostics and prognostics. The article summarizes the recent developments, but also limitations and challenges for the development of microbiome-based biomarkers for cancer early detection.