Chemotherapy Alters the Phylogenetic Molecular Ecological Networks of Intestinal Microbial Communities

Advancements in the impact of human microbiota and probiotics on leukemia

The human gut microbiota is a complex ecosystem that plays a crucial role in promoting the interaction between the body and its environment. It has been increasingly recognized that the gut microbiota has diverse physiological functions. Recent studies have shown a close association between the gut microbiota and the development of certain tumors, including leukemia. Leukemia is a malignant clonal disease characterized by the uncontrolled growth of one or more types of blood cells, which is the most common cancer in children. The imbalance of gut microbiota is linked to the pathological mechanisms of leukemia. Probiotics, which are beneficial microorganisms that help maintain the balance of the host microbiome, play a role in regulating gut microbiota. Probiotics have the potential to assist in the treatment of leukemia and improve the clinical prognosis of leukemia patients. This study reviews the relationship between gut microbiota, probiotics, and the progression of leukemia based on current research. In addition, utilizing zebrafish leukemia models in future studies might reveal the specific mechanisms of their interactions, thereby providing new insights into the clinical treatment of leukemia. In conclusion, further investigation is still needed to fully understand the accurate role of microbes in leukemia.

Uncovering Microbial Composition of the Tissue Microenvironment in Bladder Cancer using RNA Sequencing Data

Purpose: Bladder cancer (BC) is one of the top 10 common tumors in the world. It has been reported that microbiota can colonize tissues and play important roles in tumorigenesis and progression. However, the current understanding of microorganisms in the BC tissue microenvironment remains unclear. Methods: In this study, we integrated the RNA-seq data of 479 BC tissue samples from seven datasets combined with a range of bioinformatics tools to explore the landscape of microbiome in the BC tissue microenvironment. Results: The pan-microbiome was estimated to surpass 1,400 genera. A total of seven core microbiota (Bacillus, Corynebacterium, Cutibacterium, Escherichia, Halomonas, Pasteurella, and Streptomyces) were identified. Among them, Bacillus was widely distributed in all datasets with a high relative abundance (10.11% of all samples on average). Moreover, some biological factors, including tissue source and tumor grade, were found significant effects on the microbial composition of the bladder tissue. Pseudomonas, Porphyrobacter, and Acinetobacter were enriched in tumor tissues, while Mycolicibacterium and Streptomyces were enriched in patients who showed durable response to BCG therapy. In addition, we established microbial co-occurrence networks and found that the BCG therapy may attenuate the microbiological interactions. Conclusions: This study clearly provided a microbial landscape of the BC tissue microenvironment, which was important for exploring the interactions between microorganisms and BC tissues. The identified specific taxa might be potential biomarkers for BC.

Probiotic supplementation during pregnancy alters gut microbial networks of pregnant women and infants

BACKGROUND

Probiotic supplementation has been popular and widespread, yet we still lack a comprehensive understanding of how probiotic supplementation during pregnancy affects the gut microbial networks of pregnant women and infants. In this study, we firstly used network analysis to compare the gut microbiota of pregnant women with and without probiotic supplementation, as well as their infants.

METHODS

Thirty-one pairs of healthy pregnant women and infants were recruited and randomly divided into the probiotic group (15 mother-infant pairs) and the control group (16 mother-infant pairs). Pregnant women in the probiotic group consumed combined probiotics from 32 weeks to delivery. Fecal samples were collected from pregnant women and infants at several time points. Gut microbiota was evaluated using 16S rRNA gene sequencing. Intestinal microbial network and topological properties were performed using the molecular ecological network analysis.

RESULTS

No significant difference was found between the probiotic and control groups on the microbial alpha and beta diversity. As the gestational age increased, the total links, average degree, average clustering coefficient, robustness, and the proportion of positive correlations were increased in pregnant women with probiotics administration. In contrast, these indices were decreased in infants in the probiotic group.

CONCLUSION

Probiotic supplement does not change the microbial diversity of pregnant women and infants, but significantly alters the intestinal microbial network structure and properties. Although pregnant women have more complicated and stable networks after probiotic administration, their infants have less stable networks.

Gastrointestinal microbiota profile and clinical correlations in advanced EGFR-WT and EGFR-mutant non-small cell lung cancer

Introduction

Difference in clinical responses to cancer therapy in each patient is from several factors. Gastrointestinal microbiota is one of the reasons. However, this correlation remains unknown. This study aims to explore correlation between gastrointestinal microbiota profile and clinical outcomes in Thai advanced non-small cell lung cancer (NSCLC) according to epidermal growth factor receptor (EGFR) status.

Methods

We enrolled 13 patients with advanced EGFR–wild-type (WT) NSCLC who received chemotherapy and 15 patients with EGFR-mutant NSCLC who received EGFR tyrosine kinase inhibitors. We collected fecal samples at baseline and first disease evaluation and performed 16S rRNA gene sequencing by NGS to assess microbiota profile. The correlations between gastrointestinal microbiota and clinical variables were studied.

Results

The clinical characteristics were balanced between the cohorts, excluding significantly higher albumin levels in the EGFR-mutant group. Albumin was the only significant clinical factor affecting the treatment response in multivariate analysis (ORR 15.6%, P = 0.03). Proteobacteria counts were higher in the EGFR-WT group, whereas Bacteroidetes and Firmicutes counts were higher in the EGFR-mutant group. The alpha diversity of the gastrointestinal microbiome was significantly higher in the EGFR-mutant group (Shannon index: 3.82 vs. 3.25, P = 0.022). Following treatment, Proteobacteria counts were lower and Bacteroidetes and Firmicutes counts were higher in both cohorts; the changes were more prominent in the EGFR-WT cohort. No significant correlation between microbiota profile and treatment response were demonstrated in our study. However, beta diversity was significantly different according to severity of adverse events. Enrichment of Clostridia and Bacteroidia was associated with higher adverse event risk in the EGFR-WT cohort.

Conclusions

Proteobacteria was dominant in Thai lung cancer patients both EGFR-WT and EGFR-mutant, and this phylum maybe associate with lung cancer carcinogenesis. Chemotherapy altered the gastrointestinal microbiota, whereas EGFR-TKIs had less effects. Our findings highlight the potential predictive utility of the gastrointestinal microbiota for lung cancer carcinogenesis. Studies with larger cohorts and comparison with the healthy Thai population are ongoing to validate this pilot study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10050-3.

Integrated network analysis reveals that exogenous cadmium-tolerant endophytic bacteria inhibit cadmium uptake in rice

Most previous studies have focused on the diversity and species richness of microbial communities, however, understanding the interactions between species and detecting key functional members of the community can help us better understand how microorganisms perform their functions. In this study, the response of the rice plant microbial community to the inoculation of cadmium-resistant endophytic bacterium R5 (Stenotrophomonas) was investigated for the first time using a microbial phylogenetic molecular ecological network. The results showed that inoculation of R5 changed the topological characteristics of the microbial network in rice plants, with the resulting network displaying stronger complexity and interaction in roots and aboveground parts, indicating that inoculation of R5 provided favorable conditions for microbial interactions. In addition, these interactions may be related to the absorption and transportation of cadmium by rice. Under the exogenous addition of R5, the network interactions of the rice plant microbial community were more inclined to cooperation. Both in the roots and aboveground parts of rice, the plant Cd content showed a decrease as the complexity and connectivity of the network increased, suggesting that complex microbial networks may be more beneficial to rice than simple microbial networks because as they were more adaptive and resistant to unfavorable environments. After inoculation with the R5 strain, the negative interaction with Cd content in rice plants increased significantly, and there might be more synergy between the microbial community and plants to jointly inhibit the absorption and transportation of Cd.

A Pilot Study: Favorable Effects of Clostridium butyricum on Intestinal Microbiota for Adjuvant Therapy of Lung Cancer

Probiotics as medications have previously been shown to change intestinal microbial characteristics, potentially influencing cancer therapy efficacy. Patients with non-squamous non-small cell lung cancer (NS-NSCLC) treated by bevacizumab plus platinum-based chemotherapy were randomized to obtain Clostridium butyricum supplement (CBS) or receive a placebo as adjuvant therapy. Clinical efficacy and safety were assessed using progression-free survival (PFS), overall survival (OS), and adverse events (AE). Intestinal microbiota was longitudinally explored between CBS and placebo groups over time. Patients who took CBS had significantly decreased bacterial richness and abundance, as well as increased the total richness of the genus Clostridium, Bifidobacterium, and Lactobacillus compared to the placebo group (p < 0.05). Beta diversity and the interactional network of intestinal microbiota were distinctly different between CBS and placebo group. However, there were no significant variations between them in terms of microbial taxonomical taxa and alpha diversity. The potential opportunistic pathogen Shewanella was still detectable after treatment in the placebo group, while no distinguishing microbial markers were found in the CBS group. In terms of clinical efficacy, the CBS group had a significantly reduced AE compare to the placebo group (p < 0.05), although no significantly longer PFS and OS. Therefore, favorable modifications in intestinal microbiota and significant improvements in drug safety make probiotics be promising adjunctive therapeutic avenues for lung cancer treatment.

The Application of High-Throughput Technologies for the Study of Microbiome and Cancer

Human gut microbiome research, especially gut microbiome, has been developing at a considerable pace over the last decades, driven by a rapid technological advancement. The emergence of high-throughput technologies, such as genomics, transcriptomics, and others, has afforded the generation of large volumes of data, and in relation to specific pathologies such as different cancer types. The current review identifies high-throughput technologies as they have been implemented in the study of microbiome and cancer. Four main thematic areas have emerged: the characterization of microbial diversity and composition, microbial functional analyses, biomarker prediction, and, lastly, potential therapeutic applications. The majority of studies identified focus on the microbiome diversity characterization, which is reaching technological maturity, while the remaining three thematic areas could be described as emerging.

Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models

Common intestinal diseases such as Crohn’s disease (CD), ulcerative colitis (UC), and colorectal cancer (CRC) share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multidisease models. Here, we performed meta-analyses on 13 fecal metagenome data sets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple data sets of the same diseases. According to their overall trends, we grouped the disease-enriched marker species into disease-specific and disease-common clusters and revealed their distinct phylogenetic relationships; species in the CD-specific cluster were phylogenetically related, while those in the CRC-specific cluster were more distant. Strikingly, UC-specific species were phylogenetically closer to CRC, likely because UC patients have higher risk of CRC. Consistent with their phylogenetic relationships, marker species had similar within-cluster and different between-cluster metabolic preferences. A portion of marker species and pathways correlated with an indicator of leaky gut, suggesting a link between gut dysbiosis and human-derived contents. Marker species showed more coordinated changes and tighter inner-connections in cases than the controls, suggesting that the diseased gut may represent a stressed environment and pose stronger selection on gut microbes. With the marker species and pathways, we constructed four high-performance (including multidisease) models with an area under the receiver operating characteristic curve (AUROC) of 0.87 and true-positive rates up to 90%, and explained their putative clinical applications. We identified consistent microbial alterations in common intestinal diseases, revealed metabolic capacities and the relationships among marker bacteria in distinct states, and supported the feasibility of metagenome-derived multidisease diagnosis.

IMPORTANCE Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn’s disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications. To the best of our knowledge, this is the first study to construct multiclass models for these common intestinal diseases.

A Pilot Study: Changes of Intestinal Microbiota of Patients With Non-small Cell Lung Cancer in Response to Osimertinib Therapy

Osimertinib contributes to the higher efficacy and few intestinal side effects in non-small cell lung cancer (NSCLC) patients with T790M mutation. Previous studies has reported that intestinal microbiota play important roles in drug efficacy and toxicity. However, we have known less about the changes of intestinal microbiota in response to osimertinib therapy. In this pilot study, we used longitudinal sampling with 6 weeks sampling collection intervals for about 1 year to model intestinal microbial changes based on the 16S rRNA genes sequencing in fecal samples from NSCLC patients in response to osimertinib therapy. The results showed that there was no significantly different on the intestinal microbial composition at the phylum, family, and genus level among NSCLC patients with different treatment cycles (P > 0.05). There were no significant differences in alpha diversity characterized by the richness, Shannon diversity, and phylogenetic diversity based on the Welch’s t-test among NSCLC patients in response to osimertinib therapy (P > 0.05). However, the dissimilarity test and principal coordination analysis showed a few differences among NSCLC patients. The intestinal microbial markers were changed in post-therapy (Sutterella, Peptoniphilus, and Anaeroglobus) compared to that in pre-therapy (Clostridium XIVa). Furthermore, the phylogenetic molecular ecological networks (MENs) were influenced by osimertinib therapy based on the module number, link number, and module taxa composition of the first six groups. Overall, it indicated that osimertinib therapy changed the intestinal microbiota to some extent, though not completely. In all, this pilot study provides an understanding of changes of intestinal microbiota from NSCLC patients in response to osimertinib therapy. No complete changes in intestinal microbiota seem to be closely linked with the few intestinal side effects and higher efficacy in response to osimertinib therapy.

Clustering co-abundant genes identifies components of the gut microbiome that are reproducibly associated with colorectal cancer and inflammatory bowel disease

BACKGROUND

Whole-genome "shotgun" (WGS) metagenomic sequencing is an increasingly widely used tool for analyzing the metagenomic content of microbiome samples. While WGS data contains gene-level information, it can be challenging to analyze the millions of microbial genes which are typically found in microbiome experiments. To mitigate the ultrahigh dimensionality challenge of gene-level metagenomics, it has been proposed to cluster genes by co-abundance to form Co-Abundant Gene groups (CAGs). However, exhaustive co-abundance clustering of millions of microbial genes across thousands of biological samples has previously been intractable purely due to the computational challenge of performing trillions of pairwise comparisons.

RESULTS

Here we present a novel computational approach to the analysis of WGS datasets in which microbial gene groups are the fundamental unit of analysis. We use the Approximate Nearest Neighbor heuristic for near-exhaustive average linkage clustering to group millions of genes by co-abundance. This results in thousands of high-quality CAGs representing complete and partial microbial genomes. We applied this method to publicly available WGS microbiome surveys and found that the resulting microbial CAGs associated with inflammatory bowel disease (IBD) and colorectal cancer (CRC) were highly reproducible and could be validated independently using multiple independent cohorts.

CONCLUSIONS

This powerful approach to gene-level metagenomics provides a powerful path forward for identifying the biological links between the microbiome and human health. By proposing a new computational approach for handling high dimensional metagenomics data, we identified specific microbial gene groups that are associated with disease that can be used to identify strains of interest for further preclinical and mechanistic experimentation.