A normative microbiome is not restored following kidney transplantation.

Dialysis and kidney transplantation (Ktx) mitigate some of the physiological deficits in chronic kidney disease (CKD), but it remains to be determined if these mitigate microbial dysbiosis and the production of inflammatory microbial metabolites, which contribute significantly to the uraemic phenotype. We have investigated bacterial DNA signatures present in the circulation of CKD patients and those receiving a KTx. Our data are consistent with increasing dysbiosis as CKD progresses, with an accompanying increase in trimethylamine (TMA) producing pathobionts Pseudomonas and Bacillus. Notably, KTx patients displayed a significantly different microbiota compared with CKD5 patients, which surprisingly included further increase in TMA producing Bacillus and loss of salutogenic Lactobacilli. Only two genera (Viellonella and Saccharimonidales) showed significant differences in abundance following KTx that may reflect a reciprocal relationship between TMA producers and utilisers, which supersedes restoration of a normative microbiome. Our metadata analysis confirmed that TMA N-oxide (TMAO) along with one carbon metabolism had significant impact upon both inflammatory burden and the composition of the microbiome. This indicates that these metabolites are key to shaping the uraemic microbiome and might be exploited in the development of dietary intervention strategies to both mitigate the physiological deficits in CKD and enable the restoration of a more salutogenic microbiome.

Process stability in expanded granular sludge bed bioreactors enhances resistance to organic load shocks.

Environmental perturbations such as changes in organic loading rate (OLR) can have deleterious effects on the anaerobic digestion process, leading to VFA accumulation and process failure. However, the operational history of a reactor, such as prior exposure to VFA build up, can impact a reactor's resistance to shock loads. In the present study, the effects of long term (>100 days) bioreactor (un)stability on OLR shock resistance were assessed. Three 4 L EGSB bioreactors were subjected to varying levels of process stability. Operational conditions such as OLR, temperature and pH were maintained stable in R1; R2 was subjected to a series of minor OLR perturbations and R3 was subjected to a series of non-OLR perturbations, including ammonium, temperature, pH and sulfide. The effect of these different operational histories on each reactor's resistance to a sudden 8-fold increase in OLR were assessed by monitoring COD removal efficiency and biogas production. The microbial communities of each reactor were monitored using 16S rRNA gene sequencing to understand the relationship between microbial diversity and reactor stability. It was determined that the stable (un-perturbed) reactor performed best in terms of its resistance to a large OLR shock, despite its lower microbial community diversity.

Intestinal fatty acid binding protein is a disease biomarker in paediatric coeliac disease and Crohn's disease.

BACKGROUND: There is a clinical need to develop biomarkers of small bowel damage in coeliac disease and Crohn's disease. This study evaluated intestinal fatty acid binding protein (iFABP), a potential biomarker of small bowel damage, in children with coeliac disease and Crohn's disease. METHODS: The concentration iFABP was measured in plasma and urine of children with ulcerative colitis, coeliac disease, and Crohn's disease at diagnosis and from the latter two groups after treatment with gluten free diet (GFD) or exclusive enteral nutrition (EEN), respectively. Healthy children (Controls) were also recruited. RESULTS: 138 children were recruited. Plasma but not urinary iFABP was higher in patients with newly diagnosed coeliac disease than Controls (median [Q1, Q3] coeliac disease: 2104 pg/mL 1493, 2457] vs Controls: 938 pg/mL [616, 1140], p = 0.001). Plasma or urinary iFABP did not differ between patients with coeliac on GFD and Controls. Baseline iFABP in plasma decreased by 6 months on GFD (6mo GFD: 1238 pg/mL [952, 1618], p = 0.045). By 12 months this effect was lost, at which point 25% of patients with coeliac disease had detectable gluten in faeces, whilst tissue transglutaminase IgA antibodies (TGA) continued to decrease. At diagnosis, patients with Crohn's disease had higher plasma iFABP levels than Controls (EEN Start: 1339 pg/mL [895, 1969] vs Controls: 938 pg/mL [616, 1140], p = 0.008). iFABP did not differ according to Crohn's disease phenotype. Induction treatment with EEN tended to decrease (p = 0.072) iFABP in plasma which was no longer different to Controls (EEN End: 1114 pg/mL [689, 1400] vs Controls: 938 pg/mL [616, 1140], p = 0.164). Plasma or urinary iFABP did not differ in patients with ulcerative colitis from Controls (plasma iFABP, ulcerative colitis: 1309 pg/mL [1005, 1458] vs Controls: 938 pg/mL [616, 1140], p = 0.301; urinary iFABP ulcerative colitis: 38 pg/mg [29, 81] vs Controls: 53 pg/mg [27, 109], p = 0.605). CONCLUSIONS: Plasma, but not urinary iFABP is a candidate biomarker with better fidelity in monitoring compliance during GFD than TGA. The role of plasma iFABP in Crohn's disease is promising but warrants further investigation. TRIAL REGISTRATION: Clinical Trials.gov, NCT02341248. Registered on 19/01/2015.

Methanogenic granule growth and development is a continual process characterized by distinct morphological features.

Up-flow anaerobic bioreactors are widely applied for high-rate digestion of industrial wastewaters and rely on formation, and retention, of methanogenic granules, comprising of dense, fast-settling, microbial aggregates (approx. 0.5-4.0 mm in diameter). Granule formation (granulation) mechanisms have been reasonably well hypothesized and documented. However, this study used laboratory-scale bioreactors, inoculated with size-separated granular sludge to follow new granule formation, maturation, disintegration and re-formation. Temporal size profiles, volatile solids content, settling velocity, and ultrastructure of granules were determined from each of four bioreactors inoculated only with small granules, four with only large granules, and four with a full complement of naturally-size-distributed granules. Constrained granule size profiles shifted toward the natural distribution, which was associated with maximal bioreactor performance. Distinct morphological features characterized different granule sizes and biofilm development stages, including 'young', 'juvenile', 'mature' and 'old'. The findings offer opportunities toward optimizing management of high-rate, anaerobic digesters by shedding light on the rates of granule growth, the role of flocculent sludge in granulation and how shifting size distributions should be considered when setting upflow velocities.

Molecular Diagnosis of Vaginitis: Comparing Quantitative PCR and Microbiome Profiling Approaches to Current Microscopy Scoring.

Vaginitis is often diagnosed by microscopy and limited to testing for bacterial vaginosis (BV), vulvovaginal candidiasis, and trichomoniasis. Approximately 10% of vaginal swabs are negative but designated "altered flora" by BV Nugent score, leaving clinicians unsure how to treat patients. Accurate and comprehensive vaginitis diagnostics are needed to direct treatment and reduce risks of recurrent or more severe infections. Vaginal swabs were collected from 93 women (mean age, 23.53 years; range, 18 to 42 years) in a cross-sectional study. Microscopy results for BV and Candida were compared to those from two molecular approaches: (i) a comprehensive quantitative PCR (qPCR) assay, including testing for aerobic vaginitis (AV), Candida, sexually transmitted infections (STI), and BV (Applied Biosystems) with an accompanying BV interpretive algorithm (Coriell Life Sciences), and (ii) microbiome profiling of the 16S rRNA gene (Illumina). Microscopy plus BV Nugent score had 76% overall agreement with the qPCR plus BV interpretive algorithm method (24 positive, 47 negative). OF the nine samples designated altered flora by Nugent, five were categorized BV positive and four were BV negative by the qPCR method. Although BV negative, 3/4 of the latter samples had positive AV targets with one also was STI positive. Microscopic identification of Candida versus that by qPCR had 94% agreement (9 positive, 78 negative). The comprehensive qPCR assay revealed alternative etiologies summarized as 38% BV, 10% AV, 5% Candida, 2% STI, 10% mixed infection (positive targets in multiple panels), and 35% negative for all targets. 16S microbiome analysis confirmed the bacterial qPCR results and identified differentiating patterns between AV, BV, and Lactobacillus-dominated vaginal microbiomes.

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling.

BACKGROUND: In the last 5 years, the rapid pace of innovations and improvements in sequencing technologies has completely changed the landscape of metagenomic and metagenetic experiments. Therefore, it is critical to benchmark the various methodologies for interrogating the composition of microbial communities, so that we can assess their strengths and limitations. The most common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene and in the last 10 years the field has moved from sequencing a small number of amplicons and samples to more complex studies where thousands of samples and multiple different gene regions are interrogated. RESULTS: We assembled 2 synthetic communities with an even (EM) and uneven (UM) distribution of archaeal and bacterial strains and species, as metagenomic control material, to assess performance of different experimental strategies. The 2 synthetic communities were used in this study, to highlight the limitations and the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We describe an extensive survey based on synthetic communities using 3 experimental designs (fusion primers, universal tailed tag, ligated adaptors) across the 9 hypervariable 16S rDNA regions. We demonstrate that library preparation methodology can affect data interpretation due to different error and chimera rates generated during the procedure. The observed community composition was always biased, to a degree that depended on the platform, sequenced region and primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing is still quantitative, in that relative changes in abundance of taxa between samples can be recovered, despite these biases. CONCLUSION: We have assessed a range of experimental conditions across several next generation sequencing platforms using the most up-to-date configurations. We propose that the choice of sequencing platform and experimental design needs to be taken into consideration in the early stage of a project by running a small trial consisting of several hypervariable regions to quantify the discriminatory power of each region. We also suggest that the use of a synthetic community as a positive control would be beneficial to identify the potential biases and procedural drawbacks that may lead to data misinterpretation. The results of this study will serve as a guideline for making decisions on which experimental condition and sequencing platform to consider to achieve the best microbial profiling.

Extensive Modulation of the Fecal Metagenome in Children With Crohn's Disease During Exclusive Enteral Nutrition.

OBJECTIVES: Exploring associations between the gut microbiota and colonic inflammation and assessing sequential changes during exclusive enteral nutrition (EEN) may offer clues into the microbial origins of Crohn's disease (CD). METHODS: Fecal samples (n=117) were collected from 23 CD and 21 healthy children. From CD children fecal samples were collected before, during EEN, and when patients returned to their habitual diets. Microbiota composition and functional capacity were characterized using sequencing of the 16S rRNA gene and shotgun metagenomics. RESULTS: Microbial diversity was lower in CD than controls before EEN (P=0.006); differences were observed in 36 genera, 141 operational taxonomic units (OTUs), and 44 oligotypes. During EEN, the microbial diversity of CD children further decreased, and the community structure became even more dissimilar than that of controls. Every 10 days on EEN, 0.6 genus diversity equivalents were lost; 34 genera decreased and one increased during EEN. Fecal calprotectin correlated with 35 OTUs, 14 of which accounted for 78% of its variation. OTUs that correlated positively or negatively with calprotectin decreased during EEN. The microbiota of CD patients had a broader functional capacity than healthy controls, but diversity decreased with EEN. Genes involved in membrane transport, sulfur reduction, and nutrient biosynthesis differed between patients and controls. The abundance of genes involved in biotin (P=0.005) and thiamine biosynthesis decreased (P=0.017), whereas those involved in spermidine/putrescine biosynthesis (P=0.031), or the shikimate pathway (P=0.058), increased during EEN. CONCLUSIONS: Disease improvement following treatment with EEN is associated with extensive modulation of the gut microbiome.

Metagenomic Sequencing Unravels Gene Fragments with Phylogenetic Signatures of O2-Tolerant NiFe Membrane-Bound Hydrogenases in Lacustrine Sediment.

Many promising hydrogen technologies utilising hydrogenase enzymes have been slowed by the fact that most hydrogenases are extremely sensitive to O2. Within the group 1 membrane-bound NiFe hydrogenase, naturally occurring tolerant enzymes do exist, and O2 tolerance has been largely attributed to changes in iron-sulphur clusters coordinated by different numbers of cysteine residues in the enzyme's small subunit. Indeed, previous work has provided a robust phylogenetic signature of O2 tolerance [1], which when combined with new sequencing technologies makes bio prospecting in nature a far more viable endeavour. However, making sense of such a vast diversity is still challenging and could be simplified if known species with O2-tolerant enzymes were annotated with information on metabolism and natural environments. Here, we utilised a bioinformatics approach to compare O2-tolerant and sensitive membrane-bound NiFe hydrogenases from 177 bacterial species with fully sequenced genomes for differences in their taxonomy, O2 requirements, and natural environment. Following this, we interrogated a metagenome from lacustrine surface sediment for novel hydrogenases via high-throughput shotgun DNA sequencing using the Illumina™ MiSeq platform. We found 44 new NiFe group 1 membrane-bound hydrogenase sequence fragments, five of which segregated with the tolerant group on the phylogenetic tree of the enzyme's small subunit, and four with the large subunit, indicating de novo O2-tolerant protein sequences that could help engineer more efficient hydrogenases.

Microbial influencers and cotton leaf curl disease (CLCuD) susceptibility: a network perspective.

Biotic stresses, such as plant viruses, e.g., cotton leaf curl virus (CLCuV), can alter root-associated and leaf-associated microbial diversities in plants. There are complex ecological dynamics at play, with each microbe contributing to a multitude of biotic and abiotic interactions, thus deciding the stability of the plant's ecosystem in response to the disease. Deciphering these networks of interactions is a challenging task. The inferential research in microbiome is also at a nascent stage, often constrained by the underlying analytical assumptions and the limitations with respect to the depth of sequencing. There is also no real consensus on network-wide statistics to identify the influential microbial players in a network. Guided by the latest developments in network science, including recently published metrics such as Integrated View of Influence (IVI) and some other centrality measures, this study provides an exposé of the most influential nodes in the rhizospheric and phyllospheric microbial networks of the cotton leaf curl disease (CLCuD) susceptible, partially tolerant, and resistant cotton varieties. It is evident from our results that the CLCuD-resistant Gossypium arboreum possesses an equal share of keystone species, which helps it to withstand ecological pressures. In the resistant variety, the phyllosphere harbors the most influential nodes, whereas in the susceptible variety, they are present in the rhizosphere. Based on hubness score, spreading score, and IVI, the top 10 occurring keystone species in the FDH-228 (resistant) variety include Actinokineospora, Cohnella, Thermobacillus, Clostridium, Desulfofarcimen, and MDD-D21. Elusimicrobia, Clostridium-sensu-stricto_12, Candidatus woesebacteria, and Dyella were identified as the most influential nodes in the PFV-1 (partially tolerant) variety. In the PFV-2 (susceptible) variety, the keystone species were identified as Georginia, Nesterenkonia, Elusimicrobia MVP-88, Acetivibrio, Tepedisphaerales, Chelatococcus, Nitrosospira, and RCP2-54. This concept deciphers the diseased and healthy plant's response to viral disease, which may be microbially mediated.

Gut microbial ecology and exposome of a healthy Pakistani cohort.

BACKGROUND: Pakistan is a multi-ethnic society where there is a disparity between dietary habits, genetic composition, and environmental exposures. The microbial ecology of healthy Pakistani gut in the context of anthropometric, sociodemographic, and dietary patterns holds interest by virtue of it being one of the most populous countries, and also being a Lower Middle Income Country (LMIC). METHODS: 16S rRNA profiling of healthy gut microbiome of normo-weight healthy Pakistani individuals from different regions of residence is performed with additional meta-data collected through filled questionnaires. The current health status is then linked to dietary patterns through [Formula: see text] test of independence and Generalized Linear Latent Variable Model (GLLVM) where distribution of individual microbes is regressed against all recorded sources of variability. To identify the core microbiome signature, a dynamic approach is used that considers into account species occupancy as well as consistency across assumed grouping of samples including organization by gender and province of residence. Fitting neutral modeling then revealed core microbiome that is selected by the environment. RESULTS: A strong determinant of disparity is by province of residence. It is also established that the male microbiome is better adapted to the local niche than the female microbiome, and that there is microbial taxonomic and functional diversity in different ethnicities, dietary patterns and lifestyle habits. Some microbial genera, such as, Megamonas, Porphyromonas, Haemophilus, Klebsiella and Finegoldia showed significant associations with consumption of pickle, fresh fruits, rice, and cheese. Our analyses suggest current health status being associated with the diet, sleeping patterns, employment status, and the medical history. CONCLUSIONS: This study provides a snapshot of the healthy core Pakistani gut microbiome by focusing on the most populous provinces and ethnic groups residing in predominantly urban areas. The study serves a reference dataset for exploring variations in disease status and designing personalized dietary and lifestyle interventions to promote gut health, particularly in LMICs settings.

Dataset of 569 metagenome-assembled genomes from the caeca of multiple chicken breeds from commercial and backyard farming setups of Pakistan.

This article focuses the recovery of prokaryotic organisms including bacteria and archaea from 9 different groups of chicken raised in different farm setups in Pakistan. The groups comprise of three different breeds (Broilers, White Layers, and Black Australorp) of chicken raised in different farming setups that include antibiotic-free control, commercial (open and controlled shed), and backyard farms. We have recovered 569 Metagenomics-Assembled Genomes (MAGs) with a completeness of ≥50 % and contamination of ≤10 %. For each MAG, functional annotations were obtained that include KEGG modules, carbohydrate active enzymes (CAZymes), peptidases, geochemical cycles, antibiotic resistance genes, stress genes, and virulence genes. Furthermore, two different sets of Single Copy Genes (SCGs) were used to construct the phylogenetic trees. Based on the reconstructed phylogeny, phylogenetic gain of each MAG is calculated to give an account of novelty.

Network analysis of gut microbial communities reveal key genera for a multiple sclerosis cohort with Mycobacterium avium subspecies paratuberculosis infection.

BACKGROUND: In gut ecosystems, there is a complex interplay of biotic and abiotic interactions that decide the overall fitness of an individual. Divulging the microbe-microbe and microbe-host interactions may lead to better strategies in disease management, as microbes rarely act in isolation. Network inference for microbial communities is often a challenging task limited by both analytical assumptions as well as experimental approaches. Even after the network topologies are obtained, identification of important nodes within the context of underlying disease aetiology remains a convoluted task. We therefore present a network perspective on complex interactions in gut microbial profiles of individuals who have multiple sclerosis with and without Mycobacterium avium subspecies paratuberculosis (MAP) infection. Our exposé is guided by recent advancements in network-wide statistical measures that identify the keystone nodes. We have utilised several centrality measures, including a recently published metric, Integrated View of Influence (IVI), that is robust against biases. RESULTS: The ecological networks were generated on microbial abundance data (n = 69 samples) utilising 16 S rRNA amplification. Using SPIEC-EASI, a sparse inverse covariance estimation approach, we have obtained networks separately for MAP positive (+), MAP negative (-) and healthy controls (as a baseline). Using IVI metric, we identified top 20 keystone nodes and regressed them against covariates of interest using a generalised linear latent variable model. Our analyses suggest Eisenbergiella to be of pivotal importance in MS irrespective of MAP infection. For MAP + cohort, Pyarmidobacter, and Peptoclostridium were predominately the most influential genera, also hinting at an infection model similar to those observed in Inflammatory Bowel Diseases (IBDs). In MAP- cohort, on the other hand, Coprostanoligenes group was the most influential genera that reduces cholesterol and supports the intestinal barrier. CONCLUSIONS: The identification of keystone nodes, their co-occurrences, and associations with the exposome (meta data) advances our understanding of biological interactions through which MAP infection shapes the microbiome in MS individuals, suggesting the link to the inflammatory process of IBDs. The associations presented in this study may lead to development of improved diagnostics and effective vaccines for the management of the disease.

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets.

BACKGROUND: Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, the latter of which then helps retrieve their function based on annotated gene products, mRNA, protein, and metabolites. Within the context of a specific hypothesis, additional modalities are often included, to give host-microbiome interaction. For example, in human-associated microbiome projects, it has become increasingly common to include host immunology through flow cytometry. Whilst there are plenty of software approaches available, some that utilize marker-based and assembly-based approaches, for downstream statistical analyses, there is still a dearth of statistical tools that help consolidate all such information in a single platform. By virtue of stringent computational requirements, the statistical workflow is often passive with limited visual exploration. RESULTS: In this study, we have developed a Java-based statistical framework ( https://github.com/KociOrges/cviewer ) to explore shotgun metagenomics data, which integrates seamlessly with conventional pipelines and offers exploratory as well as hypothesis-driven analyses. The end product is a highly interactive toolkit with a multiple document interface, which makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant patterns. We have designed algorithms based on frequently used numerical ecology and machine learning principles, with value-driven from integrated omics tools which not only find correlations amongst different datasets but also provide discrimination based on case-control relationships. CONCLUSIONS: CViewer was used to analyse two distinct metagenomic datasets with varying complexities. These include a dietary intervention study to understand Crohn's disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean. Complete analyses of both studies in CViewer then provide very powerful mechanistic insights that corroborate with the published literature and demonstrate its full potential. Video Abstract.

Dataset of 130 metagenome-assembled genomes of healthy and diseased broiler chicken caeca from Pakistan.

This article presents metagenomic-assembled genomes (MAGs) of prokaryotic organisms originating from chicken caeca. The samples originate from broiler chickens, one group was infected with Newcastle Disease Virus (NDV) and one uninfected control group. There were four birds per group. Both groups were raised on commercially available antibiotic free feed under a semi-controlled setup. The binning step of the samples identified 130 MAGs with ≥50 % completion, and ≤10 % contamination. The data presented includes sequences in FASTA format, tables of functional annotation of genes, and data from two different approaches for phylogenetic tree construction using these MAGs. Major geochemical cycles at community level including carbon, sulfur, and nitrogen cycles are also presented.

Gut metabolome and microbiota signatures predict response to treatment with exclusive enteral nutrition in a prospective study in children with active Crohn's disease.

BACKGROUND: Predicting response to exclusive enteral nutrition (EEN) in active Crohn's disease (CD) could lead to therapy personalization and pretreatment optimization. OBJECTIVES: This study aimed to explore the ability of pretreatment parameters to predict fecal calprotectin (FCal) levels at EEN completion in a prospective study in children with CD. METHODS: In children with active CD, clinical parameters, dietary intake, cytokines, inflammation-related blood proteomics, and diet-related metabolites, metabolomics and microbiota in feces, were measured before initiation of 8 wk of EEN. Prediction of FCal levels at EEN completion was performed using machine learning. Data are presented with medians (IQR). RESULTS: Of 37 patients recruited, 15 responded (FCal < 250 µg/g) to EEN (responders) and 22 did not (nonresponders). Clinical and immunological parameters were not associated with response to EEN. Responders had lesser (µmol/g) butyrate [responders: 13.2 (8.63-18.4) compared with nonresponders: 22.3 (12.0-32.0); P = 0.03], acetate [responders: 49.9 (46.4-68.4) compared with nonresponders: 70.4 (57.0-95.5); P = 0.027], phenylacetate [responders: 0.175 (0.013-0.611) compared with nonresponders: 0.943 (0.438-1.35); P = 0.021], and a higher microbiota richness [315 (269-347) compared with nonresponders: 243 (205-297); P = 0.015] in feces than nonresponders. Responders consumed (portions/1000 kcal/d) more confectionery products [responders: 0.55 (0.38-0.72) compared with nonresponders: 0.19 (0.01-0.38); P = 0.045]. A multicomponent model using fecal parameters, dietary data, and clinical and immunological parameters predicted response to EEN with 78% accuracy (sensitivity: 80%; specificity: 77%; positive predictive value: 71%; negative predictive value: 85%). Higher taxon abundance from Ruminococcaceae, Lachnospiraceae, and Bacteroides and phenylacetate, butyrate, and acetate were the most influential variables in predicting lack of response to EEN. CONCLUSIONS: We identify microbial signals and diet-related metabolites in feces, which could comprise targets for pretreatment optimization and personalized nutritional therapy in pediatric CD.

Multidirectional scattering models for 3-dimensional ultrasound imaging.

An ultrasound image is created from backscattered echoes originating from both diffuse and directional scattering. It is potentially useful to separate these two components for the purpose of tissue characterization. This article presents several models for visualization of scattering fields on 3-dimensional (3D) ultrasound imaging. By scanning the same anatomy from multiple directions, we can observe the variation of specular intensity as a function of the viewing angle. This article considers two models for estimating the diffuse and specular components of the backscattered intensity: a modification of the well-known Phong reflection model and an existing exponential model. We examine 2-dimensional implementations and also propose novel 3D extensions of these models in which the probe is not constrained to rotate within a plane. Both simulation and experimental results show that improved performance can be achieved with 3D models.

Molecular insights informing factors affecting low temperature anaerobic applications: Diversity, collated core microbiomes and complexity stability relationships in LCFA-fed systems.

Fats, oil and grease, and their hydrolyzed counterparts-long chain fatty acids (LCFA) make up a large fraction of numerous wastewaters and are challenging to degrade anaerobically, more so, in low temperature anaerobic digestion (LtAD) systems. Herein, we perform a comparative analysis of publicly available Illumina 16S rRNA datasets generated from LCFA-degrading anaerobic microbiomes at low temperatures (10 and 20 °C) to comprehend the factors affecting microbial community dynamics. The various factors considered were the inoculum, substrate and operational characteristics, the reactor operation mode and reactor configuration, and the type of nucleic acid sequenced. We found that LCFA-degrading anaerobic microbiomes were differentiated primarily by inoculum characteristics (inoculum source and morphology) in comparison to the other factors tested. Inoculum characteristics prominently shaped the species richness, species evenness and beta-diversity patterns in the microbiomes even after long term operation of continuous reactors up to 150 days, implying the choice of inoculum needs careful consideration. The generalised additive models represented through beta diversity contour plots revealed that psychrophilic bacteria RBG-13-54-9 from family Anaerolineae, and taxa WCHB1-41 and Williamwhitmania were highly abundant in LCFA-fed microbial niches, suggesting their role in anaerobic treatment of LCFAs at low temperatures of 10-20 °C. Overall, we showed that the following bacterial genera: uncultured Propionibacteriaceae, Longilinea, Christensenellaceae R7 group, Lactivibrio, candidatus Caldatribacterium, Aminicenantales, Syntrophus, Syntrophomonas, Smithella, RBG-13-54-9, WCHB1-41, Trichococcus, Proteiniclasticum, SBR1031, Lutibacter and Lentimicrobium have prominent roles in LtAD of LCFA-rich wastewaters at 10-20 °C. This study provides molecular insights of anaerobic LCFA degradation under low temperatures from collated datasets and will aid in improving LtAD systems for treating LCFA-rich wastewaters.

A Cross-Sectional Study of Potential Antimicrobial Resistance and Ecology in Gastrointestinal and Oral Microbial Communities of Young Normoweight Pakistani Individuals.

Antimicrobial resistance (AMR) is a major global public health concern mainly affecting low- and middle-income countries (LMICs) due to lack of awareness, inadequate healthcare and sanitation infrastructure, and other environmental factors. In this study, we aimed to link microbial assembly and covariates (body mass index, smoking, and use of antibiotics) to gut microbiome structure and correlate the predictive antimicrobial gene prevalence (piARG) using PICRUSt2. We examined the gastrointestinal and oral microbial profiles of healthy adults in Pakistan through 16S rRNA gene sequencing with a focus on different ethnicities, antibiotic usage, drinking water type, smoking, and other demographic measures. We then utilised a suite of innovative statistical tools, driven by numerical ecology and machine learning, to address the above aims. We observed that drinking tap water was the main contributor to increased potential AMR signatures in the Pakistani cohort compared to other factors considered. Microbial niche breadth analysis highlighted an aberrant gut microbial signature of smokers with increased age. Moreover, covariates such as smoking and age impact the human microbial community structure in this Pakistani cohort.

A prospective study on linking diarrheagenic E. coli with stunted childhood growth in relation to gut microbiome.

Stunted growth is an emerging global challenge affecting children under the age of 5 years in low- and middle-income countries. Despite such a high global prevalence of stunting, the mechanism of pathogenesis and the role of associated gut microbiota is poorly understood. The present study was designed to investigate the association of pathogenic strains of E. coli with the residential gut microbiota of stunted growth children. A total of 64 stool sample were collected from children aged ≤ 5 years, and were processed for isolation and molecular characterization of diarrheagenic E. coli. Selected stool samples (n = 39 including three normal controls) were then analysed for microbial community profiling using 16S ribosomal RNA (rRNA) gene sequencing. Furthermore, associations between changes in the microbiota in the presence of different E. coli strains was explored. Pathotyping of the isolated E. coli (n = 64) has shown that 39.68% belonged to one of the five pathotypes of E. coli whilst the remaining ones were non-typeable. Amongst the different pathotypes, EPEC was found to be the most prevalent (52%; n = 13), followed by EAEC (20%; n = 5), EIEC (12%; n = 3), EHEC (8%; n = 2) and ETEC 2 (8%; n = 2). Phylogrouping analysis has shown that majority of the strains belonged to B2 (28.12%). Microbial diversity is shown to be significant and varied when the samples are organized under the recovered phylogroups. Moreover, based on predictive metabolism, the colonization of these strains were found to be significantly associated with energy utilization pathways such as Denovoprine-2 and glyoxylate-by. Differential analysis has shown that Escherichia-Shigella and Enterococcus were altered for the children with stunted growth.

Temporal stability and community assembly mechanisms in healthy broiler cecum.

In recent years, there has been an unprecedented advancement in in situ analytical approaches that contribute to the mechanistic understanding of microbial communities by explicitly incorporating ecology and studying their assembly. In this study, we have analyzed the temporal profiles of the healthy broiler cecal microbiome from day 3 to day 35 to recover the stable and varying components of microbial communities. During this period, the broilers were fed three different diets chronologically, and therefore, we have recovered signature microbial species that dominate during each dietary regime. Since broilers were raised in multiple pens, we have also parameterized these as an environmental condition to explore microbial niches and their overlap. All of these analyses were performed in view of different parameters such as body weight (BW-mean), feed intake (FI), feed conversion ratio (FCR), and age (days) to link them to a subset of microbes that these parameters have a bearing upon. We found that gut microbial communities exhibited strong and statistically significant specificity for several environmental variables. Through regression models, genera that positively/negatively correlate with the bird's age were identified. Some short-chain fatty acids (SCFAs)-producing bacteria, including Izemoplasmatales, Gastranaerophilales, and Roseburia, have a positive correlation with age. Certain pathogens, such as Escherichia-Shigella, Sporomusa, Campylobacter, and Enterococcus, negatively correlated with the bird's age, which indicated a high disease risk in the initial days. Moreover, the majority of pathways involved in amino acid biosynthesis were also positively correlated with the bird's age. Some probiotic genera associated with improved performance included Oscillospirales; UCG-010, Shuttleworthia, Bifidobacterium, and Butyricicoccaceae; UCG-009. In general, predicted antimicrobial resistance genes (piARGs) contributed at a stable level, but there was a slight increase in abundance when the diet was changed. To the best of the authors' knowledge, this is one of the first studies looking at the stability, complexity, and ecology of natural broiler microbiota development in a temporal setting.