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.

Microbiome-based risk prediction in incident heart failure: a community challenge.

Heart failure (HF) is a major public health problem. Early identification of at-risk individuals could allow for interventions that reduce morbidity or mortality. The community-based FINRISK Microbiome DREAM challenge (synapse.org/finrisk) evaluated the use of machine learning approaches on shotgun metagenomics data obtained from fecal samples to predict incident HF risk over 15 years in a population cohort of 7231 Finnish adults (FINRISK 2002, n=559 incident HF cases). Challenge participants used synthetic data for model training and testing. Final models submitted by seven teams were evaluated in the real data. The two highest-scoring models were both based on Cox regression but used different feature selection approaches. We aggregated their predictions to create an ensemble model. Additionally, we refined the models after the DREAM challenge by eliminating phylum information. Models were also evaluated at intermediate timepoints and they predicted 10-year incident HF more accurately than models for 5- or 15-year incidence. We found that bacterial species, especially those linked to inflammation, are predictive of incident HF. This highlights the role of the gut microbiome as a potential driver of inflammation in HF pathophysiology. Our results provide insights into potential modeling strategies of microbiome data in prospective cohort studies. Overall, this study provides evidence that incorporating microbiome information into incident risk models can provide important biological insights into the pathogenesis of HF.

Consistency across multi-omics layers in a drug-perturbed gut microbial community.

Multi-omics analyses are used in microbiome studies to understand molecular changes in microbial communities exposed to different conditions. However, it is not always clear how much each omics data type contributes to our understanding and whether they are concordant with each other. Here, we map the molecular response of a synthetic community of 32 human gut bacteria to three non-antibiotic drugs by using five omics layers (16S rRNA gene profiling, metagenomics, metatranscriptomics, metaproteomics and metabolomics). We find that all the omics methods with species resolution are highly consistent in estimating relative species abundances. Furthermore, different omics methods complement each other for capturing functional changes. For example, while nearly all the omics data types captured that the antipsychotic drug chlorpromazine selectively inhibits Bacteroidota representatives in the community, the metatranscriptome and metaproteome suggested that the drug induces stress responses related to protein quality control. Metabolomics revealed a decrease in oligosaccharide uptake, likely caused by Bacteroidota depletion. Our study highlights how multi-omics datasets can be utilized to reveal complex molecular responses to external perturbations in microbial communities.

Functional response to a microbial synbiotic in the gastrointestinal system of children: a randomized clinical trial.

BACKGROUND: Oral microbial therapy has been studied as an intervention for a range of gastrointestinal disorders. Though research suggests that microbial exposure may affect the gastrointestinal system, motility, and host immunity in a pediatric population, data have been inconsistent, with most prior studies being in neither a randomized nor placebo-controlled setting. The aim of this randomized, placebo-controlled study was to evaluate the efficacy of a synbiotic on increasing weekly bowel movements (WBMs) in constipated children. METHODS: Sixty-four children (3-17 years of age) were randomized to receive a synbiotic (n = 33) comprising mixed-chain length oligosaccharides and nine microbial strains, or placebo (n = 31) for 84 days. Stool microbiota was analyzed on samples collected at baseline and completion. The primary outcome was a change from baseline of WBMs in the treatment group compared to placebo. RESULTS: Treatment increased (p < 0.05) the number of WBMs in children with low baseline WBMs, despite broadly distinctive baseline microbiome signatures. Sequencing revealed that low baseline microbial richness in the treatment group significantly anticipated improvements in constipation (p = 0.00074). CONCLUSIONS: These findings suggest the potential for (i) multi-species-synbiotic interventions to improve digestive health in a pediatric population and (ii) bioinformatics-based methods to predict response to microbial interventions in children. IMPACT: Synbiotic microbial treatment improved the number of spontaneous weekly bowel movements in children compared to placebo. Intervention induced an increased abundance of bifidobacteria in children, compared to placebo. All administered probiotic species were enriched in the gut microbiome of the intervention group compared to placebo. Baseline microbial richness demonstrated potential as a predictive biomarker for response to intervention.

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.

Calorie restriction improves metabolic state independently of gut microbiome composition: a randomized dietary intervention trial.

BACKGROUND: The gut microbiota has been suggested to play a significant role in the development of overweight and obesity. However, the effects of calorie restriction on gut microbiota of overweight and obese adults, especially over longer durations, are largely unexplored. METHODS: Here, we longitudinally analyzed the effects of intermittent calorie restriction (ICR) operationalized as the 5:2 diet versus continuous calorie restriction (CCR) on fecal microbiota of 147 overweight or obese adults in a 50-week parallel-arm randomized controlled trial, the HELENA Trial. The primary outcome of the trial was the differential effects of ICR versus CCR on gene expression in subcutaneous adipose tissue. Changes in the gut microbiome, which are the focus of this publication, were defined as exploratory endpoint of the trial. The trial comprised a 12-week intervention period, a 12-week maintenance period, and a final follow-up period of 26 weeks. RESULTS: Both diets resulted in ~5% weight loss. However, except for Lactobacillales being enriched after ICR, post-intervention microbiome composition did not significantly differ between groups. Overall weight loss was associated with significant metabolic improvements, but not with changes in the gut microbiome. Nonetheless, the abundance of the Dorea genus at baseline was moderately predictive of subsequent weight loss (AUROC of 0.74 for distinguishing the highest versus lowest weight loss quartiles). Despite the lack of consistent intervention effects on microbiome composition, significant study group-independent co-variation between gut bacterial families and metabolic biomarkers, anthropometric measures, and dietary composition was detectable. Our analysis in particular revealed associations between insulin sensitivity (HOMA-IR) and Akkermansiaceae, Christensenellaceae, and Tanerellaceae. It also suggests the possibility of a beneficial modulation of the latter two intestinal taxa by a diet high in vegetables and fiber, and low in processed meat. CONCLUSIONS: Overall, our results suggest that the gut microbiome remains stable and highly individual-specific under dietary calorie restriction. TRIAL REGISTRATION: The trial, including the present microbiome component, was prospectively registered at ClinicalTrials.gov NCT02449148 on May 20, 2015.

Enrichment of gut microbiome strains for cultivation-free genome sequencing using droplet microfluidics.

We report a droplet microfluidic method to target and sort individual cells directly from complex microbiome samples and to prepare these cells for bulk whole-genome sequencing without cultivation. We characterize this approach by recovering bacteria spiked into human stool samples at a ratio as low as 1:250 and by successfully enriching endogenous Bacteroides vulgatus to the level required for de novo assembly of high-quality genomes. Although microbiome strains are increasingly demanded for biomedical applications, a vast majority of species and strains are uncultivated and without reference genomes. We address this shortcoming by encapsulating complex microbiome samples directly into microfluidic droplets and amplifying a target-specific genomic fragment using a custom molecular TaqMan probe. We separate those positive droplets by droplet sorting, selectively enriching single target strain cells. Finally, we present a protocol to purify the genomic DNA while specifically removing amplicons and cell debris for high-quality genome sequencing.

Delivery of Metabolically Neuroactive Probiotics to the Human Gut.

The human microbiome is a rich factory for metabolite production and emerging data has led to the concept that orally administered microbial strains can synthesize metabolites with neuroactive potential. Recent research from ex vivo and murine models suggests translational potential for microbes to regulate anxiety and depression through the gut-brain axis. However, so far, less emphasis has been placed on the selection of specific microbial strains known to produce the required key metabolites and the formulation in which microbial compositions are delivered to the gut. Here, we describe a double-capsule technology to deliver high numbers of metabolically active cells derived from the 24-strain probiotic product SH-DS01 to the gastrointestinal tract, including the small intestine, where immune responses and adsorption of metabolites into the bloodstream occur. Based on its genome sequence, Limosilactobacillus reuteri SD-LRE2-IT was predicted to have the genetic capacity to de novo produce a specific metabolite of interest to brain health, vitamin B12, which could be confirmed in vitro. Taken together, our data conceptualizes the importance of rationally defined microbial strain characterization based on genomics and metabolomics data, combined with carefully designed capsule technology for delivery of live cells and concomitant functionality in and beyond the gut ecosystem.

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 .

The Complex Genetic Landscape of Hereditary Ataxias in Turkey and Implications in Clinical Practice.

BACKGROUND: The genetic and epidemiological features of hereditary ataxias have been reported in several populations; however, Turkey is still unexplored. Due to high consanguinity, recessive ataxias are more common in Turkey than in Western European populations. OBJECTIVE: To identify the prevalence and genetic structure of hereditary ataxias in the Turkish population. METHODS: Our cohort consisted of 1296 index cases and 324 affected family members. Polymerase chain reaction followed by Sanger sequencing or fragment analysis were performed to screen for the trinucleotide repeat expansions in families with a dominant inheritance pattern, as well as in sporadic cases. The expansion in the frataxin (FXN) gene was tested in all autosomal recessive cases and in sporadic cases with a compatible phenotype. Whole-exome sequencing was applied to 251 probands, selected based on the family history, age of onset, and phenotype. RESULTS: Mutations in known ataxia genes were identified in 30% of 1296 probands. Friedreich's ataxia was found to be the most common recessive ataxia in Turkey, followed by autosomal recessive spastic ataxia of Charlevoix-Saguenay. Spinocerebellar ataxia types 2 and 1 were the most common dominant ataxias. Whole-exome sequencing was performed in 251 probands with an approximate diagnostic yield of 50%. Forty-eight novel variants were found in a plethora of genes, suggesting a high heterogeneity. Variants of unknown significance were discussed in light of clinical data. CONCLUSION: With the large sample size recruited across the country, we consider that our results provide an accurate picture of the frequency of hereditary ataxias in Turkey. © 2021 International Parkinson and Movement Disorder Society.

Revisiting the complex architecture of ALS in Turkey: Expanding genotypes, shared phenotypes, molecular networks, and a public variant database.

The last decade has proven that amyotrophic lateral sclerosis (ALS) is clinically and genetically heterogeneous, and that the genetic component in sporadic cases might be stronger than expected. This study investigates 1,200 patients to revisit ALS in the ethnically heterogeneous yet inbred Turkish population. Familial ALS (fALS) accounts for 20% of our cases. The rates of consanguinity are 30% in fALS and 23% in sporadic ALS (sALS). Major ALS genes explained the disease cause in only 35% of fALS, as compared with ~70% in Europe and North America. Whole exome sequencing resulted in a discovery rate of 42% (53/127). Whole genome analyses in 623 sALS cases and 142 population controls, sequenced within Project MinE, revealed well-established fALS gene variants, solidifying the concept of incomplete penetrance in ALS. Genome-wide association studies (GWAS) with whole genome sequencing data did not indicate a new risk locus. Coupling GWAS with a coexpression network of disease-associated candidates, points to a significant enrichment for cell cycle- and division-related genes. Within this network, literature text-mining highlights DECR1, ATL1, HDAC2, GEMIN4, and HNRNPA3 as important genes. Finally, information on ALS-related gene variants in the Turkish cohort sequenced within Project MinE was compiled in the GeNDAL variant browser (www.gendal.org).

Effects of Weight-Loss Interventions on Short-Chain Fatty Acid Concentrations in Blood and Feces of Adults: A Systematic Review.

Short-chain fatty acids (SCFAs, mainly acetate, propionate, and butyrate), which are primarily derived from the gut microbiome, may exert anti-inflammatory and immunomodulatory effects, and regulate energy homeostasis. It has been suggested that weight loss may affect SCFA metabolism, but a systematic review of intervention studies is lacking. We aimed to systematically assess the effects of dietary, physical activity-based, and surgical weight-loss interventions among overweight [body mass index (BMI) 25-29.9 kg/m2)] or obese (BMI ≥30 kg/m2) adults (≥18 y) on concentrations of acetate, propionate, butyrate, and total SCFAs in blood, urine, or feces. We conducted a systematic literature search in PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials (CENTRAL) up to April 30, 2018 for randomized and nonrandomized weight-loss trials among overweight or obese adults, in which the concentrations of individual and total SCFAs were assessed. A total of 9 studies consisting of 2 randomized parallel-arm trials, 4 crossover trials, and 3 nonrandomized clinical or surgical trials were included. In the majority of studies, changes in fecal SCFA concentrations were assessed, whereas changes in serum SCFAs were reported from 1 trial. Individual and total SCFA concentrations either remained unchanged or decreased significantly following weight loss. Three of the dietary interventions that resulted in decreased SCFA concentrations were low (≤5% of energy) in total carbohydrates. Most of the studies had a high risk of bias. Decreases in SCFA concentrations may accompany weight loss induced by bariatric surgery or dietary restriction among overweight or obese adults, particularly when carbohydrate intake is reduced. However, findings were inconsistent and based on studies with high to unclear risk of bias, and small sample sizes. Because measurements of fecal SCFAs may not be ideal due to limited sample standardization, well-powered trials with repeated blood measurements of SCFAs are required. This review was registered at PROSPERO as CRD42018088716.

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.

A novel homozygous DJ1 mutation causes parkinsonism and ALS in a Turkish family.

OBJECTIVE: DJ1 mutations (PARK7) are among the monogenic causes of early-onset autosomal recessive parkinsonism. Here, we report clinical and genetic findings in a family with Turkish origin carrying a new DJ1 mutation and presenting with early-onset levodopa responsive parkinsonism and signs of amyotrophic lateral sclerosis (ALS). METHODS: The family consisted of 12 members including 10 offsprings of whom three were affected. All family members underwent detailed clinical examination. DNA samples from the index case, his unaffected sister, and his parents were subjected to whole genome sequencing analysis. RESULTS: The index case 38-year-old man developed left hand tremor at the age of 24 years. He had progressive asymmetrical parkinsonism, depression and developed signs of ALS within 4 years. His two affected sisters had young-onset asymmetrical tremor-dominant parkinsonism with signs of ALS. A new homozygous p.Q45X mutation in exon 3 in DJ1 was found in all three patients. Their unaffected parents and one clinically healthy sibling were found to be heterozygous for this mutation. CONCLUSIONS: This is the second report of DJ1 mutations associated with parkinsonism and ALS. This is relevant for genetic counseling as well as for understanding the pathogenesis of the broad spectrum of parkinsonism-ALS disease complex.

The distinct genetic pattern of ALS in Turkey and novel mutations.

The frequency of amyotrophic lateral sclerosis (ALS) mutations has been extensively investigated in several populations; however, a systematic analysis in Turkish cases has not been reported so far. In this study, we screened 477 ALS patients for mutations, including 116 familial ALS patients from 82 families and 361 sporadic ALS (sALS) cases. Patients were genotyped for C9orf72 (18.3%), SOD1 (12.2%), FUS (5%), TARDBP (3.7%), and UBQLN2 (2.4%) gene mutations, which together account for approximately 40% of familial ALS in Turkey. No SOD1 mutations were detected in sALS patients; however, C9orf72 (3.1%) and UBQLN2 (0.6%) explained 3.7% of sALS in the population. Exome sequencing revealed mutations in OPTN, SPG11, DJ1, PLEKHG5, SYNE1, TRPM7, and SQSTM1 genes, many of them novel. The spectrum of mutations reflect both the distinct genetic background and the heterogeneous nature of the Turkish ALS population.

Turkish families with juvenile motor neuron disease broaden the phenotypic spectrum of SPG11.

OBJECTIVE: Identification of causative mutations in 3 consanguineous families (with 4 affected members) referred to our center with young-onset motor neuron disease and overlapping phenotypes resembling autosomal recessive juvenile amyotrophic lateral sclerosis (ARJALS) and autosomal recessive hereditary spastic paraplegia (ARHSP). METHODS: Patients have a slowly progressive motor neuron disease with upper and lower motor neuron dysfunction. There is distal muscle weakness and atrophy associated with pyramidal signs. Whole-exome sequencing was performed on the patients and the unaffected parent samples to identify disease-causing mutations. Variants were prioritized according to their predicted pathogenicity and their relevance to the clinical phenotypes. RESULTS: Five distinct homozygous mutations within the SPG11 gene were identified, 3 of which were novel and truncating: c.7155T>G/p.Tyr2385Ter, c.2250delT/p.Phe750Leufs*3, and c.1966_1967delAA/p.Lys656Valfs*11. The copresence of 2 distinct homozygous missense variations was observed in 2 families: c.6224A>G/p.Asn2075Ser and c.7132T>C/p.Phe2378Leu. The segregation of these variations in the family members was validated by Sanger sequencing. CONCLUSIONS: Four patients with juvenile-onset motor neuron disease with consanguineous parents were found to carry homozygous mutations in the SPG11 gene. Our findings confirm the overlapping phenotypes of SPG11-based ARJALS and ARHSP, indicating that these 2 entities may be the extreme phenotypes of the same disease continuum with many common features. This, in turn, confirms the difficult differential diagnosis of these 2 diseases in the clinic.