Dysbiosis and Associated Stool Features Improve Prediction of Response to Biological Therapy in Inflammatory Bowel Disease.

BACKGROUND & AIMS: Dysbiosis of the gut microbiota is considered a key contributor to inflammatory bowel disease (IBD) etiology. Here, we investigated potential associations between microbiota composition and the outcomes to biological therapies. METHODS: The study prospectively recruited 296 patients with active IBD (203 with Crohn's disease, 93 with ulcerative colitis) initiating biological therapy. Quantitative microbiome profiles of pretreatment and posttreatment fecal samples were obtained combining flow cytometry with 16S amplicon sequencing. Therapeutic response was assessed by endoscopy, patient-reported outcomes, and changes in fecal calprotectin. The effect of therapy on microbiome variation was evaluated using constrained ordination methods. Prediction of therapy outcome was performed using logistic regression with 5-fold cross-validation. RESULTS: At baseline, 65.9% of patients carried the dysbiotic Bacteroides2 (Bact2) enterotype, with a significantly higher prevalence among patients with ileal involvement (76.8%). Microbiome variation was associated with the choice of biological therapy rather than with therapeutic outcome. Only anti-tumor necrosis factor-α treatment resulted in a microbiome shift away from Bact2, concomitant with an increase in microbial load and butyrogen abundances and a decrease in potentially opportunistic Veillonella. Remission rates for patients hosting Bact2 at baseline were significantly higher with anti-tumor necrosis factor-α than with vedolizumab (65.1% vs 35.2%). A prediction model, based on anthropometrics and clinical data, stool features (microbial load, moisture, and calprotectin), and Bact2 detection predicted treatment outcome with 73.9% accuracy for specific biological therapies. CONCLUSION: Fecal characterization based on microbial load, moisture content, calprotectin concentration, and enterotyping may aid in the therapeutic choice of biological therapy in IBD.

Real-time PCR-based quantitative microbiome profiling elucidates the microbial dynamic succession in backslopping fermentation of Taiwanese pickled cabbage.

BACKGROUND: Microbiota succession determines the flavor and quality of fermented foods. Quantitative PCR-based quantitative microbiome profiling (QMP) has been applied broadly for microbial analysis from absolute abundance perspectives, transforming microbiota ratios into counts by normalizing 16S ribosomal RNA (16S rRNA) gene sequencing data with gene copies quantified by quantitative PCR. However, the application of QMP in fermented foods is still limited. RESULTS: QMP elucidated microbial succession of Taiwanese pickled cabbage. In the spontaneous first-round fermentation (FR), the 16S rRNA gene copies of total bacteria increased from 6.1 to 10 log copies mL-1. The dominant lactic acid bacteria genera were successively Lactococcus, Leuconostoc and Lactiplantibacillus. Despite the decrease in the proportion of Lactococcus during the succession, the absolute abundance of Lactococcus still increased. In the backslopping second-round fermentation (SR), the total bacteria 16S rRNA gene copies increased from 7.6 to 9.9 log copies mL-1. The addition of backslopping starter and vinegar rapidly led to a homogenous microbial community dominated by Lactiplantibacillus. The proportion of Lactiplantibacillus remained consistently around 90% during SR, whereas its absolute abundance exhibited a continuous increase. In SR without vinegar, Leuconostoc consistently dominated the fermentation. CONCLUSION: The present study highlights that compositional analysis would misinterpret microbial dynamics, whereas QMP reflected the real succession profiles and unveiled the essential role of vinegar in promoting Lactiplantibacillus dominance in backslopping fermentation of Taiwanese pickled cabbage. Quantitative microbiome profiling (QMP) was found to be a more promising approach for the detailed observation of microbiome succession in food fermentation compared to compositional analysis. © 2024 Society of Chemical Industry.

Challenges and perspectives of quantitative microbiome profiling in food fermentations.

Spontaneously fermented foods are consumed and appreciated for thousands of years although they are usually produced with fluctuated productivity and quality, potentially threatening both food safety and food security. To guarantee consistent fermentation productivity and quality, it is essential to control the complex microbiota, the most crucial factor in food fermentations. The prerequisite for the control is to comprehensively understand the structure and function of the microbiota. How to quantify the actual microbiota is of paramount importance. Among various microbial quantitative methods evolved, quantitative microbiome profiling, namely to quantify all microbial taxa by absolute abundance, is the best method to understand the complex microbiota, although it is still at its pioneering stage for food fermentations. Here, we provide an overview of microbial quantitative methods, including the development from conventional methods to the advanced quantitative microbiome profiling, and the application examples of these methods. Moreover, we address potential challenges and perspectives of quantitative microbiome profiling methods, as well as future research needs for the ultimate goal of rational and optimal control of microbiota in spontaneous food fermentations. Our review can serve as reference for the traditional food fermentation sector for stable fermentation productivity, quality and safety.

A gelatinized lipopeptide diet effectively modulates immune response, disease resistance and gut microbiome in Penaeus vannamei challenged with Vibrio parahaemolyticus.

Penaeus vannamei is one of the most economically vital shrimp globally, but infectious diseases have hampered its proper production and supply. As antibiotics pose a huge threat to the environment and humankind, it is essential to seek an alternative strategy to overcome infection and ensure proper culture and production. The present study investigates the effect of an anti-infective biosurfactant derivative lipopeptide MSA31 produced by a marine bacterium on the growth performance, disease resistance, and the gut microbiome of P. vannamei when challenged with pathogenic Vibrio parahaemolyticus SF14. The shrimp were fed with a commercial and lipopeptide formulated diet for 60 days and the growth performance was analyzed. The lipopeptide fed shrimp group showed enhanced growth performance and specific growth rate with improved weight gain than the control group. The challenge experiment showed that the survival rate was significant in the lipopeptide fed group compared to the control group. The results revealed 100% mortality in the control group at the end of 12 h of challenge, while 50% of the lipopeptide diet-fed group survived 24 h, which indicates the enhanced disease resistance in shrimp fed with a lipopeptide diet. The test group also showed higher levels of digestive and immune enzymes, which suggests that the lipopeptide diet could positively modulate the digestive and immune activity of the shrimp. The gut microbiome profiling by Illumina high-throughput sequencing revealed that the most abundant genera in the lipopeptide diet-fed group were Adhaeribacter, Acidothermus, Brevibacillus, Candidatus, Mycobacterium, Rodopila, and Streptomyces, while opportunistic pathogens such as Streptococcus, Escherichia, Klebsiella, Neisseria, Rhizobium, and Salmonella were abundant in the control diet-fed shrimp. Also, lipopeptide diet-fed shrimp were found to have a high abundance of ammonia and nitrogen oxidizing bacteria, which are essential pollutant degraders. Therefore, the study reveals that the dietary supplementation of lipopeptide in shrimp aquaculture could positively modulate the gut microbiome and enhance the shrimp's overall health and immunity in an eco-friendly manner.

Chinese Liquor Fermentation: Identification of Key Flavor-Producing Lactobacillus spp. by Quantitative Profiling with Indigenous Internal Standards.

Identifying the functional microbes in spontaneous food fermentation is important for improving food quality. To identify the key flavor producers in Chinese liquor fermentation, we propose a novel quantitative microbiome profiling method that uses indigenous internal standards to normalize high-throughput amplicon sequencing results. We screened Lactobacillus acetotolerans and Lactobacillus jinshani as indigenous internal standards based on their high distribution frequencies and relative abundances. After determining the absolute abundance of indigenous internal standards using quantitative PCR with species-specific primers, the liquor-fermented bacterial community and its dynamics were better characterized by internal standards normalization. Based on quantitative microbiome profiling, we identified that Lactobacillus was a key flavor producer correlated with eight flavor compounds. Metatranscriptomic analysis indicated that Lactobacillus was active in transcribing genes involving the biosynthesis of flavor compounds and their precursors. This work has developed a novel and extensible absolute quantification method for microbiota that will alleviate concerns in the statistical analyses based on relative microbiome profiling, and shed insights into the function of Lactobacillus in food fermentation. It can potentially be applied to other microbial ecology studies.IMPORTANCE In this study, we developed a novel strategy using indigenous internal standards to normalize the high-throughput amplicon sequencing results. We chose two Lactobacillus species as indigenous internal standards and characterized the absolute abundance of the bacterial community. Further, we identified Lactobacillus as the key flavor producer using quantitative microbiome profiling combined with multivariate statistics and metatranscriptomic analysis. This work developed a novel strategy for absolute quantitative abundance analysis of microbiota and expanded our understanding of the role of Lactobacillus in food fermentation.

A Necrotizing Enterocolitis-Associated Gut Microbiota Is Present in the Meconium: Results of a Prospective Study.

BACKGROUND: Anomalous intestinal microbiota development is supposedly associated with development of necrotizing enterocolitis (NEC). Our aim in this study was to identify the intestinal microbiota of patients at risk for NEC. METHODS: In a prospective trial that investigated prognostic factors for development of NEC in high-risk neonates (NTR4153), 11 NEC cases were gestational age/birthweight matched with controls (ratio of 1:2). Feces were collected twice a week. We used the first feces sample of each patient (meconium), as well as the last 2 feces samples prior to development of NEC. DNA was extracted, and the bacterial 16S rRNA genes were analyzed on a MiSeq sequencer. RESULTS: The presence and abundance of Clostridium perfringens (8.4%) and Bacteroides dorei (0.9%) in meconium were increased in neonates who developed NEC compared with controls (0.1% and 0.2%; both species, P < .001). In post-meconium samples, the abundance of staphylococci became negatively associated with NEC development (P = .1 and P = .01 for consecutive samples); Clostridium perfringens continued to be more prevalent in NEC cases. Early enteral feeding and, in particular, breast milk were correlated with an increase in lactate-producing bacilli in post-meconium samples (ρ = -0.45; P = .004). CONCLUSIONS: A NEC-associated gut microbiota can be identified in meconium samples; C. perfringens continues to be associated with NEC from the first meconium till just before NEC onset. In contrast, in post-meconium, increased numbers of staphylococci were negatively associated with NEC. These findings suggest causality but this causality should be verified in trials of induced infection in animals, targeted antibiotics, and/or probiotics. CLINICAL TRIALS REGISTRATION: CALIFORNIA trial, registered under trial number NTR4153 in the Dutch Trial Registry.

Saponin treatment for eukaryotic DNA depletion alters the microbial DNA profiles by reducing the abundance of Gram-negative bacteria in metagenomics analyses.

Background: Recent advances in microbiome sequencing techniques have provided new insights into the role of the microbiome on human health with potential diagnostic implications. However, these developments are often hampered by the presence of a large amount of human DNA interfering with the analysis of the bacterial content. Nowadays, extensive scientific literature focuses on eukaryotic DNA depletion methods, which successfully remove host DNA in microbiome studies, even if a precise assessment of the impact on bacterial DNA is often missing. Methods: Here, we have investigated a saponin-based DNA isolation protocol commonly applied to different biological matrices to deplete the released host DNA. Results: The bacterial DNA obtained was used to assess the relative abundance of bacterial and human DNA, revealing that the inclusion of 2.5% wt/vol saponin allowed the depletion of most of the host's DNA in favor of bacterial DNA enrichment. However, shotgun metagenomic sequencing showed inaccurate microbial profiles of the DNA samples, highlighting an erroneous increase in Gram-positive DNA. Even the application of 0.0125% wt/vol saponin altered the bacterial profile by depleting Gram-negative bacteria, resulting in an overall increase of Gram-positive bacterial DNA. Conclusion: The application of the saponin-based protocol drastically changes the detection of the microbial composition of human-related biological specimens. In this context, we revealed that saponin targets not only host cells but also specific bacterial cells, thus inducing a drastic reduction in the profiling of Gram-negative bacterial DNA.

Missing microbes in infants and children in the COVID-19 pandemic: a study of 1,126 participants in Beijing, China.

The COVID-19 pandemic has caused many fatalities worldwide and continues to affect the health of the recovered patients in the form of long-COVID. In this study, we compared the gut microbiome of uninfected infants and children before the pandemic began (BEFORE cohort, n=906) to that of after the pandemic (AFTER cohort, n=220) to examine the potential impact of social distancing and life habit changes on infant/children gut microbiome. Based on 16S rRNA sequencing, we found a significant change in microbiome composition after the pandemic, with Bacteroides enterotype increasing to 35.45% from 30.46% before the pandemic. qPCR quantification indicated that the bacterial loads of seven keystone taxa decreased by 91.69%-19.58%. Quantitative microbiome profiling, used to enhance the resolution in detecting microbiome differences, revealed a greater explained variance of pandemic on microbiome compared to gender, as well as a significant decrease in bacterial loads in 15 of the 20 major genera. The random forest age-predictor indicated the gut microbiomes were less mature in the after-pandemic cohort than in the before-pandemic cohort in the children group (3-12 years old) and had features of a significantly younger age (average of 1.86 years). Lastly, body weight and height were significantly lower in the after-pandemic cohort than in the before-pandemic cohort in infants (<1 year of age), which was associated with a decrease in bacterial loads in the fecal microbiome.

Decoding the microbiome for sustainable agriculture.

Root-associated microbiota profoundly affect crop health and productivity. Plants can selectively recruit beneficial microbes from the soil and actively balance microbe-triggered plant-growth promotion and stress tolerance enhancement. The cost associated with this is the root-mediated support of a certain number of specific microbes under nutrient limitation. Thus, it is important to consider the dynamic changes in microbial quantity when it comes to nutrient condition-induced root microbiome reassembly. Quantitative microbiome profiling (QMP) has recently emerged as a means to estimate the specific microbial load variation of a root microbiome (instead of the traditional approach quantifying relative microbial abundances) and data from the QMP approach can be more closely correlated with plant development and/or function. However, due to a lack of detailed-QMP data, how soil nutrient conditions affect quantitative changes in microbial assembly of the root-associated microbiome remains poorly understood. A recent study quantified the dynamics of the soybean root microbiome, under unbalanced fertilization, using QMP and provided data on the use of specific synthetic communities (SynComs) for sustaining crop productivity. In this editorial, we explore potential opportunities for utilizing QMP to decode the microbiome for sustainable agriculture.

Skin locations inference and body fluid identification from skin microbial patterns for forensic applications.

Given that microbiological analysis can be an alternative method that overcomes the shortcomings of traditional forensic technology, and skin samples may be the most common source of cases, the analysis of skin microbiome was investigated in this study. High-throughput sequencing targeting the V3-V4 region of 16S rRNA gene was performed to reveal the skin microbiome of healthy individuals in Guangdong Han. The bacterial diversity of the palm, navel, groin and plantar of the same individual was analyzed. The overall classification based on 16S rRNA gene amplicons revealed that the microbial composition of skin samples from different anatomical parts was different, and the dominant bacterial genus of the navel, plantar, groin and palm skin were dominated by Cutibacterium, Staphylococcus, Corynebacterium and Staphylococcus, respectively. PCoA analysis showed that the skin at these four anatomical locations could only be grouped into three clusters. A predictive model based on random forest algorithm showed the potential to accurately distinguish these four anatomical locations, which indicated that specific bacteria with low abundance were the key taxa. In addition, the skin microbiome in this study is significantly different from the dominant microbiome in saliva and vaginal secretions identified in our previous study, and can be distinguished from these two tissue fluids. In conclusion, the present findings on the community and microbial structure details of the human skin may reveal its potential application value in assessing the location of skin samples and the type of body fluids in forensic medicine.

A tool to assess the mock community samples in 16S rRNA gene-based microbiota profiling studies.

Inclusion and investigation of technical controls in microbiome sequencing studies is important for understanding technical biases and errors. Here, we present chkMocks, a general R-based tool that allows researchers to compare the composition of mock communities that are processed along with samples to their theoretical composition. A visual comparison between experimental and theoretical community composition and their correlation is provided for researchers to assess the quality of their sample processing workflows.

Quantitative microbiome profiling reveals the developmental trajectory of the chicken gut microbiota and its connection to host metabolism.

Revealing the assembly and succession of the chicken gut microbiota is critical for a better understanding of its role in chicken physiology and metabolism. However, few studies have examined dynamic changes of absolute chicken gut microbes using the quantitative microbiome profiling (QMP) method. Here, we revealed the developmental trajectory of the broiler chicken gut bacteriome and mycobiome by combining high-throughput sequencing with a microbial load quantification assay. We showed that chicken gut microbiota abundance and diversity reached a plateau at 7 days posthatch (DPH), forming segment-specific community types after 1 DPH. The bacteriome was more impacted by deterministic processes, and the mycobiome was more affected by stochastic processes. We also observed stage-specific microbes in different gut segments, and three microbial occurrence patterns including "colonization," "disappearance," and "core" were defined. The microbial co-occurrence networks were very different among gut segments, with more positive associations than negative associations. Furthermore, we provided links between the absolute changes in chicken gut microbiota and their serum metabolite variations. Time-course untargeted metabolomics revealed six metabolite clusters with different changing patterns of abundance. The foregut microbiota had more connections with chicken serum metabolites, and the gut microbes were closely related to chicken lipid and amino acid metabolism. The present study provided a full landscape of chicken gut microbiota development in a quantitative manner, and the associations between gut microbes and chicken serum metabolites further highlight the impact of gut microbiota in chicken growth and development.

aMeta: an accurate and memory-efficient ancient metagenomic profiling workflow.

Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMeta, an accurate metagenomic profiling workflow for ancient DNA designed to minimize the amount of false discoveries and computer memory requirements. Using simulated data, we benchmark aMeta against a current state-of-the-art workflow and demonstrate its superiority in microbial detection and authentication, as well as substantially lower usage of computer memory.

Assessing the Performance of a Novel Stool-Based Microbiome Test That Predicts Response to First Line Immune Checkpoint Inhibitors in Multiple Cancer Types.

The intestinal microbiome is by now an undebatable key player in the clinical outcome of ICI therapies. However, no microbiome profiling method to aid therapy decision is yet validated. We conducted a multi-centric study in patients with stage III/IV melanoma, NSCLC, or RCC receiving ICI treatment. The stool microbiome profile of 63 patients was analyzed with BiomeOne®, a microbiome-based algorithm that anticipates whether a patient will achieve clinical benefit with ICIs prior to therapy initiation. Classification of patient samples as Rs and NRs was achieved with a sensitivity of 81% and a specificity of 50% in this validation cohort. An ICI-favorable response was characterized by an intestinal microbiome rich in bacteria such as Oscillospira sp., Clostridia UCG-014, Lachnospiraceae UCG-010 sp., Prevotella copri, and a decrease in Sutterella sp., Lactobacillales, and Streptococcus sp. Patients who developed immune-related adverse events (irAEs) had an overall increased microbial diversity and richness, and a stool microbiome depleted in Agathobacter. When compared with the programmed death-ligand 1 (PD-L1) expression test in the subcohort of NSCLC patients (n = 38), BiomeOne® exhibited a numerically higher sensitivity (78.6%) in identifying responders when compared with the PD-L1 test (67.9%). This study provides an evaluation of BiomeOne®, the first microbiome-based test for prediction of ICI response, to achieve market authorization. Validation with further indications and expansion to other microbiome-based interventions will be essential to bring microbiome-based diagnostics into standard clinical practice.

Gut microbiota response to in vitro transit time variation is mediated by microbial growth rates, nutrient use efficiency and adaptation to in vivo transit time.

BACKGROUND: Transit time is an important modulator of the human gut microbiome. The inability to modify transit time as the sole variable hampers mechanistic in vivo microbiome research. We singled out gut transit time in an unprecedented in vitro approach by subjecting faecal microbial communities from six individuals with either short, medium or long in vivo transit times, to three different colonic transit times of 21, 32 and 63 h in the validated human gut in vitro model, SHIME. RESULTS: Transit time was identified as the single most important driver of microbial cell concentrations (52%), metabolic activity (45%) and quantitative (24%) and proportional (22%) community composition. Deceleration of transit was characterised by a significant decrease of specific Bifidobacterium and Veillonella spp. and increase of specific fibre degrading bacteria and nutrient specialists, such as Bacteroides, Prevotella, Ruminococcus, Bilophila and Akkermansia spp. These microbial communities reached a higher population density and net carbohydrate fermentation, leading to an increased SCFA production at longer transit times. In contrast, the carbohydrate-to-biomass production efficiency was increased at shorter transits, particularly in well-adapted faecal microbiomes from donors with short in vivo transit. Said adaptation was also reflected in the carbohydrate-to-SCFA conversion efficiency which varied with donor, but also colon region and SCFA chain length. A long transit time promoted propionate production, whereas butyrate production and butyrate producers were selectively enriched in the proximal colon at medium transit time. CONCLUSION: Microbial growth rates and nutrient utilisation efficiency mediate the species-specific gut microbiota response to in vitro transit time variation, which is the main driver of in vitro microbial load, metabolism and community composition. Given the in vivo transit time variation within and between individuals, the personalisation of in vitro transit time based on in vivo data is required to accurately study intra- and inter-individual differences in gut microbiome structure, functionality and interactions with host and environmental modulators. Video Abstract.

Impaired Mucosal Homeostasis in Short-Term Fiber Deprivation Is Due to Reduced Mucus Production Rather Than Overgrowth of Mucus-Degrading Bacteria.

The gut mucosal environment is key in host health; protecting against pathogens and providing a niche for beneficial bacteria, thereby facilitating a mutualistic balance between host and microbiome. Lack of dietary fiber results in erosion of the mucosal layer, suggested to be a result of increased mucus-degrading gut bacteria. This study aimed to use quantitative analyses to investigate the diet-induced imbalance of mucosal homeostasis. Seven days of fiber-deficiency affected intestinal anatomy and physiology, seen by reduced intestinal length and loss of the colonic crypt-structure. Moreover, the mucus layer was diminished, muc2 expression decreased, and impaired mucus secretion was detected by stable isotope probing. Quantitative microbiome profiling of the gut microbiota showed a diet-induced reduction in bacterial load and decreased diversity across the intestinal tract, including taxa with fiber-degrading and butyrate-producing capabilities. Most importantly, there was little change in the absolute abundance of known mucus-degrading bacteria, although, due to the general loss of taxa, relative abundance would erroneously indicate an increase in mucus degraders. These findings underscore the importance of using quantitative methods in microbiome research, suggesting erosion of the mucus layer during fiber deprivation is due to diminished mucus production rather than overgrowth of mucus degraders.

Microbiome of Citrullus colocynthis (L.) Schrad. Reveals a Potential Association with Non-Photosynthetic Cyanobacteria.

Citrullus colocynthis grows in the sandy desert soil of the Arabian Peninsula with limited access to water, aside from occasional precipitation or dew. Understanding its ability to produce water-filled fruit and nutrient-rich seeds despite the harsh environment, can be useful for agricultural applications. However, information regarding the microbiome of C. colocynthis is lacking. We hypothesized that C. colocynthis associates with bacteria that aid its survival, like what has been observed in other desert plants. Here, we used 16S rRNA gene data to gain insight into the microbiome of C. colocynthis to identify its associated bacteria. In total, 9818 and 6983 OTUs were generated from root, soil, and leaf samples combined. Overall, bulk soils had the highest alpha diversity, followed by rhizosphere and root zone soils. Furthermore, C. colocynthis is associated with known plant-growth-promoting bacteria (including Acidobacteria, Bacterioidetes, and Actinobacteria), and interestingly a class of non-photosynthetic Cyanobacteria (Melainabacteria) that is more abundant on the inside and outside of the root surface than control samples, suggesting its involvement in the rhizophagy process. This study will provide a foundation for functional studies to further understand how C. colocynthis-microbes interactions help them grow in the desert, paving the path for possible agricultural applications.

Cross-comparison of microbiota in the oropharynx, hypopharyngeal squamous cell carcinoma and their adjacent tissues through quantitative microbiome profiling.

Aims: To clarify the absolute abundance of microbial communities on hypopharyngeal squamous cell carcinoma and their correlation to those in the oropharynx. Methods: Clinical data, swabs, and tissue samples from 27 HPSCC patients were collected in this study and divided into three sampling groups: 19 oropharyngeal mucosa (OPM), 27 hypopharyngeal carcinomas tissues (HC), and 26 corresponding adjacent tissues (AT). Relative microbiome profiling (RMP), and quantitative microbiome profiling (QMP) of 16S rRNA amplicon sequencing were used for analysis. Results: Beta-diversity showed that abundance and phylogenetic tree in OPM group were less when compared to either HC and AT. Although HC and AT were found to have similar microbiota, Bray-Curtis based beta-diversity still highlighted differences. Fusobacterium, Porphyromonas, Haemophilus, and Peptostreptococcus at the genus level in OPM were positively correlated with HC. After categorizing HC through TNM staging, the abundance of genera Fusobacterium, Parvimonas, and Dialister were found to be enhanced in higher T classifications (T3-4) and advanced stages (Ⅳ). Conclusions: QMP yielded more comprehensive results than RMP. Dysbiosis was found in OPM groups and could be used to narrow down differential microbiome for the HC group. Genera of Parvimonas, Fusobacterium, and Dialister were deemed asrisk factors of advanced HPSCC.

The supplementation of a prebiotic improves the microbial community in the gut and the skin of Atlantic salmon (Salmo salar).

Aquaculture growth is hindered by an increasing number of challenges, primarily infectious diseases and inappropriate or unsustainable fish nutrition. Hence it is critical to develop novel prevention strategies to minimise infectious diseases and pharmaceutical interventions. Nutritional challenges and the health of the fish could be improved by managing their microbial communities. Microbiomes can play a crucial role in fish physiology, particularly in digestion, by metabolizing largely indigestible feed components for the host or synthesis essential micronutrients. Beyond their nutritional role, microbiomes are considered the first line of defence against pathogens. In this study, a novel prebiotic mix (Selectovit), composed of 1,3/1,6-beta glucans, mannan-oligosaccharides, nucleic acids, nucleotides, medium chain fatty acids and single chain fatty acids, was tested at different inclusion levels (0.0; 0.5; 1.0; 2.0 g/kg) in the diet of Atlantic salmon (Salmo salar). Using experimental feed trials and 16 S rRNA microbiome profiling, the impact of the prebiotic blend on fish growth and microbial community within both the gastrointestinal tract and the skin was assessed. Overall, the supplement showed no significant impact on growth. However, we clearly demonstrate that the prebiotic can significantly manipulate the microbial community of the distal intestine and the skin. Several potential beneficial bacteria such as Bacillus and Mycoplasma spp. were significantly more abundant in the prebiotic-fed groups compared to the control. In contrast, putative pathogenic bacteria were less abundant in the salmon fed the prebiotic blend. Interestingly, the supplement induced more changes in the skin than in the gut. There is growing evidence in fish for highly complex interactions between the microbial communities of the digestive system and external mucosa, and with the host immune system. Further research in this field could lead to the creation of novel bacterial biomarkers and new non-invasive strategies for fish digestive health monitoring.

Optimized bacterial DNA isolation method for microbiome analysis of human tissues.

Recent advances in microbiome sequencing have rendered new insights into the role of the microbiome in human health with potential clinical implications. Unfortunately, the presence of host DNA in tissue isolates has hampered the analysis of host-associated bacteria. Here, we present a DNA isolation protocol for tissue, optimized on biopsies from resected human colons (~2-5 mm in size), which includes reduction of human DNA without distortion of relative bacterial abundance at the phylum level. We evaluated which concentrations of Triton and saponin lyse human cells and leave bacterial cells intact, in combination with DNAse treatment to deplete released human DNA. Saponin at a concentration of 0.0125% in PBS lysed host cells, resulting in a 4.5-fold enrichment of bacterial DNA while preserving the relative abundance of Firmicutes, Bacteroidetes, γ-Proteobacteria, and Actinobacteria assessed by qPCR. Our optimized protocol was validated in the setting of two large clinical studies on 521 in vivo acquired colon biopsies of 226 patients using shotgun metagenomics. The resulting bacterial profiles exhibited alpha and beta diversities that are similar to the diversities found by 16S rRNA amplicon sequencing. A direct comparison between shotgun metagenomics and 16S rRNA amplicon sequencing of 15 forceps tissue biopsies showed similar bacterial profiles and a similar Shannon diversity index between the sequencing methods. Hereby, we present the first protocol for enriching bacterial DNA from tissue biopsies that allows efficient isolation of all bacteria. Our protocol facilitates analysis of a wide spectrum of bacteria of clinical tissue samples improving their applicability for microbiome research.