Correlation between invasive microbiota in margin-surrounding mucosa and anastomotic healing in patients with colorectal cancer

Collagenase-producing bacteria are common in anastomotic leakage after colorectal surgery: a systematic review

PURPOSE

Some gut bacteria can produce enzymes (collagenases) that can break down collagen in the intestinal wall. This could be a part of the pathophysiology of anastomotic leakage (AL). This systematic review aimed to investigate if such bacteria were present more frequently in AL patients versus non-AL patients following colorectal surgery.

METHODS

This systematic review was reported according to the PRISMA and AMSTAR guidelines. Before the literature search, a study protocol was registered at PROSPERO (CRD42022363454). We searched PubMed, EMBASE, Google Scholar, and Cochrane CENTRAL on April 9th, 2023, for randomized and observational human studies of AL following colorectal surgery with information on gastrointestinal bacteria. The primary outcome was bacteria with the potential to produce collagenase. The risk of bias was assessed with the Newcastle-Ottawa Scale, as all studies were observational.

RESULTS

We included 15 studies, with a total of 52,945 patients, of which 1,747 had AL, and bacteriological information from feces, mucosa, the resected specimen, or drain fluid was presented. In 10 of the 15 studies, one or more collagenase-producing bacteria were identified in the patients with AL. Neither the bacteria nor the collagenase production were quantified in any of the studies. The studies varied greatly in terms of sample material, analytical method, and time of collection. Studies using DNA sequencing methods did not report findings of collagenase-producing bacteria.

CONCLUSION

Collagenase-producing bacteria are more common in patients with AL following colorectal surgery than in patients without AL, but the significance is unclear. From the current studies, it is not possible to determine the pathogenicity of the individual gut bacteria.

Diagnosis of Crohn's disease and ulcerative colitis using the microbiome

BACKGROUND

Inflammatory bowel disease (IBD) is a multifactorial chronic inflammatory disease resulting from dysregulation of the mucosal immune response and gut microbiota. Crohn's disease (CD) and ulcerative colitis (UC) are difficult to distinguish, and differential diagnosis is essential for establishing a long-term treatment plan for patients. Furthermore, the abundance of mucosal bacteria is associated with the severity of the disease. This study aimed to differentiate and diagnose these two diseases using the microbiome and identify specific biomarkers associated with disease activity.

RESULTS

Differences in the abundance and composition of the microbiome between IBD patients and healthy controls (HC) were observed. Compared to HC, the diversity of the gut microbiome in patients with IBD decreased; the diversity of the gut microbiome in patients with CD was significantly lower. Sixty-eight microbiota members (28 for CD and 40 for UC) associated with these diseases were identified. Additionally, as the disease progressed through different stages, the diversity of the bacteria decreased. The abundances of Alistipes shahii and Pseudodesulfovibrio aespoeensis were negatively correlated with the severity of CD, whereas the abundance of Polynucleobacter wianus was positively correlated. The severity of UC was negatively correlated with the abundance of A. shahii, Porphyromonas asaccharolytica and Akkermansia muciniphilla, while it was positively correlated with the abundance of Pantoea candidatus pantoea carbekii. A regularized logistic regression model was used for the differential diagnosis of the two diseases. The area under the curve (AUC) was used to examine the performance of the model. The model discriminated UC and CD at an AUC of 0.873 (train set), 0.778 (test set), and 0.633 (validation set) and an area under the precision-recall curve (PRAUC) of 0.888 (train set), 0.806 (test set), and 0.474 (validation set).

CONCLUSIONS

Based on fecal whole-metagenome shotgun (WMS) sequencing, CD and UC were diagnosed using a machine-learning predictive model. Microbiome biomarkers associated with disease activity (UC and CD) are also proposed.

Dialister pneumosintes and aortic graft infection - a case report

BACKGROUND

Dialister pneumosintes is an anaerobic, Gram negative bacillus, found in the human oral cavity and associated with periodontitis. It has also been isolated from gastric mucosa and stool samples. Recent case reports implicate D. pneumosintes in local infection such as dental root canals, sinusitis, Lemierres syndrome and brain abscesses, as well as distal infections of the liver and lung through haematogenous spread.

CASE PRESENTATION

We present a novel case of aortic graft infection and aortoenteric fistula (AEF) in a 75 year old Caucasian male, associated with D. pneumosintes bacteraemia. Microbiological evaluation of septic emboli in the lower limbs revealed other gastrointestinal flora. This suggests either AEF leading to graft infection and subsequent distal emboli and bacteraemia, or a dental origin of infection which seeded to the graft, resulting in AEF and systemic infection. To our knowledge this is the first report of D. pneumosintes associated aortic graft infection. The patient underwent surgical explantation, oversew of the aorta and placement of extra-anatomical bypass graft in conjunction with antimicrobial therapy, making a good recovery with discharge home after a 35-day hospital admission.

CONCLUSION

We report a case of Dialister pneumosintes bacteraemia associated with aortic graft infection. To our knowledge, vascular graft-associated infection with D. pneumosintes has not been reported before.

The Influence of the Microbiome on Anastomotic Leak

Anastomotic leak, defined by the International Study Group of Rectal Cancer as "a communication between the intra- and extraluminal compartments owing to a defect of the integrity of the intestinal wall at the anastomosis," is one of the most devastating complications in colorectal surgery. Much work has been done to identify causes of leak; however, despite advances in surgical technique, the prevalence of anastomotic leak has remained at around 11%. The potential causative role of bacteria in the etiopathology of anastomotic leak was established in the 1950s. More recently, alterations in the colonic microbiome have been shown to affect rates of anastomotic leak. Multiple perioperative factors that alter the homeostasis of the gut microbiota community structure and function have been linked to anastomotic leak after colorectal surgery. Here, we discuss the role of diet, radiation, bowel preparation, medications including nonsteroidal anti-inflammatory drugs, morphine, and antibiotics, and specific microbial pathways that have been implicated in anastomotic leak via their effects on the microbiome.

Baohe pill decoction for diarrhea induced by high-fat and high-protein diet is associated with the structure of lactase-producing bacterial community

Background

This study investigated the effects of Baohe pill decoction on the diversity and community composition of lactase-producing bacteria in the intestinal contents of mice with diarrhea induced by high-fat and high-protein diet, which provided an experimental basis for the study on the therapeutic mechanism of Baohe pill decoction.

Materials and methods

The Traditional Chinese Medicine Systems Pharmacology (TCMSP), DisGeNET, UniProt, National Center for Biotechnology Information (NCBI), and GeneCards databases were used to collect the potential targets with active ingredients of Baohe pill decoction, diarrhea, and lactase, and then construct correlation networks. Fifteen Kunming mice were randomly divided into the control group (CN), natural recovery group (NR), and Baohe pill decoction treatment group (BHP), with five mice in each group. After constructing a mouse diarrhea model by HFHPD induction, BHP was gavaged with Baohe pill decoction, and the other groups were gavaged with distilled water of equal. The intestinal contents were collected from ileal to jejunal and analyzed using metagenomic sequencing to characterize the intestinal content of lactase-producing bacteria in mice.

Results

The core active ingredients related to diarrhea in Baohe pill decoction were quercetin, luteolin, kaempferol, forsythin, and wogonin. And there was no intersection between the potential targets with the active ingredient of Baohe pill, lactase, and diarrhea. After the intervention of Baohe pill decoction, the Observed species, Chao1 index, and Operational Taxonomic Units (OTU) number increased in BHP (P > 0.05), while the Pielous evenness and Shannon index decreased (P > 0.05). In Beta diversity, the community structure of the NR was significantly different from CN and BHP (P < 0.05), and the community structure of the CN was not significant difference from BHP (P > 0.05). Compared to NR, the relative abundance of Bifidobacterium and Amycolatopsis increased, while the relative abundance of Lachnoclostridium, Sinorhizobium, Cedecea, and Escherichia decreased in BHP, but none of the significant differences (P > 0.05).

Conclusion

The therapeutic effect of Baohe pill decoction on diarrhea induced by HFHPD does not appear to involve the body’s lactase gene targets directly, but is associated with the change of the construction of lactase-producing bacterial communities.

A systematic review of microbial markers for risk prediction of colorectal neoplasia

BACKGROUND

Substantial evidence indicates that dysbiosis of the gut microbial community is associated with colorectal neoplasia. This review aims to systematically summarise the microbial markers associated with colorectal neoplasia and to assess their predictive performance.

METHODS

A comprehensive literature search of MEDLINE and EMBASE databases was performed to identify eligible studies. Observational studies exploring the associations between microbial biomarkers and colorectal neoplasia were included. We also included prediction studies that constructed models using microbial markers to predict CRC and adenomas. Risk of bias for included observational and prediction studies was assessed.

RESULTS

Forty-five studies were included to assess the associations between microbial markers and colorectal neoplasia. Nine faecal microbiotas (i.e., Fusobacterium, Enterococcus, Porphyromonas, Salmonella, Pseudomonas, Peptostreptococcus, Actinomyces, Bifidobacterium and Roseburia), two oral pathogens (i.e., Treponema denticola and Prevotella intermedia) and serum antibody levels response to Streptococcus gallolyticus subspecies gallolyticus were found to be consistently associated with colorectal neoplasia. Thirty studies reported prediction models using microbial markers, and 83.3% of these models had acceptable-to-good discrimination (AUROC > 0.75). The results of predictive performance were promising, but most of the studies were limited to small number of cases (range: 9-485 cases) and lack of independent external validation (76.7%).

CONCLUSIONS

This review provides insight into the evidence supporting the association between different types of microbial species and their predictive value for colorectal neoplasia. Prediction models developed from case-control studies require further external validation in high-quality prospective studies. Further studies should assess the feasibility and impact of incorporating microbial biomarkers in CRC screening programme.

Human disease prediction from microbiome data by multiple feature fusion and deep learning

Human disease prediction from microbiome data has broad implications in metagenomics. It is rare for the existing methods to consider abundance profiles from both known and unknown microbial organisms, or capture the taxonomic relationships among microbial taxa, leading to significant information loss. On the other hand, deep learning has shown unprecedented advantages in classification tasks for its feature-learning ability. However, it encounters the opposite situation in metagenome-based disease prediction since high-dimensional low-sample-size metagenomic datasets can lead to severe overfitting; and black-box model fails in providing biological explanations. To circumvent the related problems, we developed MetaDR, a comprehensive machine learning-based framework that integrates various information and deep learning to predict human diseases. Experimental results indicate that MetaDR achieves competitive prediction performance with a reduction in running time, and effectively discovers the informative features with biological insights.

Metabolomic Comparison of Patients With Colorectal Cancer at Different Anticancer Treatment Stages

Background

The difficulties of early diagnosis of colorectal cancer (CRC) result in a high mortality rate. The ability to predict the response of a patient to surgical resection or chemotherapy may be of great value for clinicians when planning CRC treatments. Metabolomics is an emerging tool for biomarker discovery in cancer research. Previous reports have indicated that the metabolic profile of individuals can be significantly altered between CRC patients and healthy controls. However, metabolic changes in CRC patients at different treatment stages have not been explored.

Methods

To this end, we performed nuclear magnetic resonance (NMR)-based metabolomic analysis to determine metabolite aberrations in CRC patients before and after surgical resection or chemotherapy. In general, a total of 106 urine samples from four clinical groups, namely, healthy volunteers (n = 31), presurgery CRC patients (n = 25), postsurgery CRC patients (n = 25), and postchemotherapy CRC patients (n = 25), were collected and subjected to further analysis.

Results

In the present study, we identified five candidate metabolites, namely, N-phenylacetylglycine, succinate, 4-hydroxyphenylacetate, acetate, and arabinose, in CRC patients compared with healthy individuals, three of which were reported for the first time. Furthermore, approximately ten metabolites were uniquely identified at each stage of CRC treatment, serving as good candidates for biomarker panel selection.

Conclusion

In summary, these potential metabolite candidates may provide promising early diagnostic and monitoring approaches for CRC patients at different anticancer treatment stages.

Proteomic and microbial assessments on the effect of Antrodia cinnamomea in C57BL/6 mice

Antrodia cinnamomea (AC) is a nutraceutical fungus and studies have suggested that AC has the potential to prevent or alleviate diseases. However, little is known about the AC-induced phenotypes on the intestine-liver axis and gut microbial alterations. Here, we performed two-dimensional difference gel electrophoresis (2D-DIGE) and MALDI-Biotyper to elaborate the AC-induced phenotypes on the intestine-liver axis and gut microbial distribution of C57BL/6 mice. The experimental outcomes showed that the hepatic density may increase by elevating hepatic redox regulation, lipid degradation and glycolysis-related proteins and alleviating cholesterol biosynthesis and transport-related proteins in C57BL/6 mice with AC treatment. Moreover, AC facilitates intestinal glycolysis, TCA cycle, redox and cytoskeleton regulation-related proteins, but also reduces intestinal vesicle transport-related proteins in C57BL/6 mice. However, the body weight, GTT, daily food/water intake, and fecal/urine weight were unaffected by AC supplementation in C57BL/6 mice. Notably, the C57BL/6-AC mice had a higher gut microbial abundance of Alistipes shahii (AS) than C57BL/6-Ctrl mice. In summary, the AC treatment affects intestinal permeability by regulating redox and cytoskeleton-related proteins and elevates the gut microbial abundance of AS in C57BL/6 mice that might be associated with increasing hepatic density and metabolism-related proteins of the liver in C57BL/6 mice. Our study provides an insight into the mechanisms of AC-induced phenotypes and a comprehensive assessment of AC's nutraceutical effect in C57BL/6 mice.

Microbiome Patterns in Matched Bile, Duodenal, Pancreatic Tumor Tissue, Drainage, and Stool Samples: Association with Preoperative Stenting and Postoperative Pancreatic Fistula Development

Postoperative complications after pancreatic surgery are still a significant problem in clinical practice. The aim of this study was to characterize and compare the microbiomes of different body compartments (bile duct, duodenal mucosa, pancreatic tumor lesion, postoperative drainage fluid, and stool samples; preoperative and postoperative) in patients undergoing pancreatic surgery for suspected pancreatic cancer, and their association with relevant clinical factors (stent placement, pancreatic fistula, and gland texture). For this, solid (duodenal mucosa, pancreatic tumor tissue, stool) and liquid (bile, drainage fluid) biopsy samples of 10 patients were analyzed using 16s rRNA gene next-generation sequencing. Our analysis revealed: (i) a distinct microbiome in the different compartments, (ii) markedly higher abundance of Enterococcus in patients undergoing preoperative stent placement in the common bile duct, (iii) significant differences in the beta diversity between patients who developed a postoperative pancreatic fistula (POPF B/C), (iv) patients with POPF B/C were more likely to have bacteria belonging to the genus Enterococcus, and (v) differences in microbiome composition with regard to the pancreatic gland texture. The structure of the microbiome is distinctive in different compartments, and can be associated with the development of a postoperative pancreatic fistula.

Best practices in bowel preparation for colorectal surgery: a 2020 overview

INTRODUCTION

Cohort studies have recently initiated a paradigm shift in the field of preoperative bowel preparation. Indeed, the adjunction of oral antibiotics (OAB) to mechanical bowel preparation (MBP) is now the gold standard for the American guidelines. However, this strategy is highly controverted.

AREAS COVERED

This review was an up-to-date analysis of literature on bowel preparation. We conducted a systematic review for randomized controlled trials (RCTs) and meta-analyses published since 2009. A non-exhaustive overview of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) cohort studies and the international guidelines was also given, and future leads were discussed.

EXPERT OPINION

The methodology of the ACS NSQIP studies did not allow a strong conclusion in favor of the association MBP+OAB. Besides, guidelines were not univocal, with non-American guidelines promoting no preparation at all. RCTs favored OAB alone: indeed, MBP+OAB showed no benefits in terms of surgical site infection (SSI) except when compared to MBP alone, while OAB alone seemed superior to no preparation. Likewise, the meta-analyses also favored OAB alone in terms of overall SSI and organ space infection. Large RCTs are currently running and may change these conclusions. Finally, microbiota is a future lead for personalized OAB.