Assessing the Fecal Microbiota: An Optimized Ion Torrent 16S rRNA Gene-Based Analysis Protocol

Assessing the distribution of 16S rRNA gene sequences within a biological sample represents the current state-of-the-art for determination of human gut microbiota composition. Advances in dissecting the microbial biodiversity of this ecosystem have very much been dependent on the development of novel high-throughput DNA sequencing technologies, like the Ion Torrent. However, the precise representation of this bacterial community may be affected by the protocols used for DNA extraction as well as by the PCR primers employed in the amplification reaction. Here, we describe an optimized protocol for 16S rRNA gene-based profiling of the fecal microbiota.     

Clinical Characteristics,Etiology and Antimicrobial Susceptibility among Overweight and Obese Individuals with Diarrhea: Observed at a Large Diarrheal Disease Hospital,Bangladesh

Background

The present study aimed to determine the clinical characteristics and etiology of overweight and obese (OO) individuals with diarrhea attending an urban Dhaka Hospital, International Centre for Diarrheal Disease Research (icddr,b), Bangladesh.

Methods

Total of 508 under-5 children, 96 individuals of 5–19 years and 1331 of >19 years were identified as OO from the Diarrheal Disease Surveillance System (DDSS) between 1993–2011. Two comparison groups such as well-nourished and malnourished individuals from respective age stratums were selected.

Results

Isolation rate of rotavirus was higher among OO under-5 children compared to malnourished group (46% vs. 28%). Rotavirus infection among OO individuals aged 5–19 years (9% vs. 3%) (9% vs. 3%) and >19 years (6% vs. 4%) (6% vs. 3%) was higher compared to well-nourished and malnourished children. Conversely, Vibrio cholerae was lower among all OO age groups compared to well-nourished and malnourished ones. Shigella (4% vs. 6%) (4% vs. 8%), and Campylobacter (3% vs. 5%) (3% vs. 5%) were lower only among OO in >19 years individuals compared to their counterparts of the same age stratum. Salmonella was similarly isolated in all age strata and nutritional groups. In multinomial logistic regression among under-5 children, significant association was observed only with use of antimicrobials at home [OR-1.97] and duration of hospital stay [OR-0.68]. For individuals aged 5–19 years, use of antimicrobials at home (OR-1.83), some or severe dehydration (OR-3.12), having received intravenous saline (OR-0.46) and rotavirus diarrhea (OR-2.96) were found to be associated with OO respectively. Moreover, significant associations were also found for duration of diarrhea before coming to hospital (>24 hours) (OR-1.24), Shigella (OR-0.46), and Campylobacter (OR-0.58) among >19 years OO individuals along with other associated co-variates in 5–19 years group (all p<0.05).

Conclusion and significance

Higher proportion of OO were infected with rotavirus and a greater proportion of them used antimicrobials before coming to the hospital.     

Fusing Data Mining,Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

Background

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study.

Methods

The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators.

Results

After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001).

Conclusion

The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.     

Leaf wax n‐alkane patterns of six tropical montane tree species show species‐specific environmental response

It remains poorly understood how the composition of leaf wax n‐alkanes reflects the local environment. This knowledge gap inhibits the interpretation of plant responses to the environment at the community level and, by extension, inhibits the applicability of n‐alkane patterns as a proxy for past environments. Here, we studied the n‐alkane patterns of five Miconia species and one Guarea species, in the Ecuadorian Andes (653–3,507 m a.s.l.). We tested for species‐specific responses in the average chain length (ACL), the C₃₁/(C₃₁ + C₂₉) ratio (ratio), and individual odd n‐alkane chain lengths across an altitudinally driven environmental gradient (mean annual temperature, mean annual relative air humidity, and mean annual precipitation). We found significant correlations between the environmental gradients and species‐specific ACL and ratio, but with varying magnitude and direction. We found that the n‐alkane patterns are species‐specific at the individual chain length level, which could explain the high variance in metrics like ACL and ratio. Although we find species‐specific sensitivity and responses in leaf n‐alkanes, we also find a general decrease in “shorter” (<C₂₉) and an increase in “longer” (>C₃₁) chain lengths with the environmental gradients, most strongly with temperature, suggesting n‐alkanes are useful for reconstructing past environments.     

Proteomic and microarray analyses of the Dictyostelium Zak1-GSK-3 signaling pathway reveal a role in early development

GskA, the Dictyostelium GSK-3 orthologue, is modified and activated by the dual-specificity tyrosine kinase Zak1, and the two kinases form part of a signaling pathway that responds to extracellular cyclic AMP. We identify potential cellular effectors for the two kinases by analyzing the corresponding null mutants. There are proteins and mRNAs that are altered in abundance in only one or the other of the two mutants, indicating that each kinase has some unique functions. However, proteomic and microarray analyses identified a number of proteins and genes, respectively, that are similarly misregulated in both mutant strains. The positive correlation between the array data and the proteomic data is consistent with the Zak1-GskA signaling pathway's functioning by directly or indirectly regulating gene expression. The discoidin 1 genes are positively regulated by the pathway, while the abundance of the H5 protein is negatively regulated. Two of the targets, H5 and discoidin 1, are well-characterized markers for early development, indicating that the Zak1-GskA pathway plays a role in development earlier than previously observed.     

A novel in vitro propagation system for West Indian elm [Guazuma ulmifolia Lam. (Malvaceae)]: a valuable medicinal woody species

In Vitro Cellular & Developmental Biology - Plant - The aim of this study was to establish a system of in vitro germination and propagation of Guazuma ulmifolia Lam. microcuttings (Malvaceae)....     

Phyllachora species infecting maize and other grass species in the Americas represents a complex of closely related species

The genus Phyllachora contains numerous obligate fungal parasites that produce raised, melanized structures called stromata on their plant hosts referred to as tar spot. Members of this genus are known to infect many grass species but generally do not cause significant damage or defoliation, with the exception of P. maydis which has emerged as an important pathogen of maize throughout the Americas, but the origin of this pathogen remains unknown. To date, species designations for Phyllachora have been based on host associations and morphology, and most species are assumed to be host specific. We assessed the sequence diversity of 186 single stroma isolates collected from 16 hosts representing 15 countries. Samples included both herbarium and contemporary strains that covered a temporal range from 1905 to 2019. These 186 isolates were grouped into five distinct species with strong bootstrap support. We found three closely related, but genetically distinct groups of Phyllachora are capable of infecting maize in the United States, we refer to these as the P. maydis species complex. Based on herbarium specimens, we hypothesize that these three groups in the P. maydis species complex originated from Central America, Mexico, and the Caribbean. Although two of these groups were only found on maize, the third and largest group contained contemporary strains found on maize and other grass hosts, as well as herbarium specimens from maize and other grasses that include 10 species of Phyllachora. The herbarium specimens were previously identified based on morphology and host association. This work represents the first attempt at molecular characterization of Phyllachora species infecting grass hosts and indicates some Phyllachora species can infect a broad range of host species and there may be significant synonymy in the Phyllachora genus.