Development of workflow for picornavirus genome sequence analysis

Picornaviruses are small, non-enveloped, icosahedral, positive stranded RNA viruses and among the most common human pathogens. Some of the clinically important genera for humans are Enterovirus, Hepatovirus, Parechovirus and Cardiovirus. The symptoms for tthe picornaviral infections range from mild, asymptomatic to fatal disease. Threats posed to human health by these viruses is observedd in the constant outbreaks of enteroviruses and parechoviruses in the different parts of the world. Next generation sequencing provides an efficient way to detect and identify known or novel micro-organisms. Advantages of NGS are rapid sequencing methods, high-throughput process and affordable costs. On the other hand, NGS also requires advanced technical and computational skills, and creates a bottleneck owing to necessity of standardization of bioinformatic tools. It is therefore imperative to optimize and determine parameters, which provide accuracy in every stage of NGS workflow. The aim of this thesis was to develop a rapid and straightforward, user-friendly workflow for the assembly and analysis of picornaviral genomes. Chipster platform was chosen as the primary test platform. The workflow involved use of automated analysis pipelines (VirusDetect and A5 assembly pipeline), and alternative approaches, which included pre-processing of raw data, and reference-mapping or de novo assembly (Velvet and SPAdes) of picornavirus sequences. Except for de novo assembly and validation and quality assessment of final outputs, all steps were performed in Chipster. Of these approaches, VirusDetect and reference-mapping were not successful. A5 pipeline for microbial genome assembly was found to be very suited for picornavirus identification. Velvet and SPAdes also performed well, but Velvet assembler was found to more computationally exhaustive and time consuming. Quality assessment suggested that performance of SPAdes was relatively better than the performance of A5 or Velvet. As A5 pipeline does not require any parameter settings, it can be used as initila identification and contig/scaffold generation method for picornaviral sequences. Together with implementation of de novo assembler(s) on Chipster platform a novel, user-friendly NGS workflow for picornavirus sequence assembly can be established

Gut microbiota composition and function in pregnancy as determinants of prediabetes at two-year postpartum

AimsDeep metagenomics offers an advanced tool for examining the relationship between gut microbiota composition and function and the onset of disease; in this case, does the composition and function of gut microbiota during pregnancy differ in women who develop prediabetes and those who do not at two-year postpartum, and whether the gut microbiota composition associates with glycemic traits.MethodsIn total, 439 women were recruited in early pregnancy. Gut microbiota was assessed by metagenomics analysis in early (13.9 +/- 2.0 gestational weeks) and late pregnancy (35.1 +/- 1.0 gestational weeks). Prediabetes was determined using American Diabetes Association criteria as fasting plasma glucose 5.6-6.9 mmol/l analyzed by an enzymatic hexokinase method. Of the women, 39 (22.1%) developed prediabetes by two-year postpartum.ResultsThe relative abundances of Escherichia unclassified (FDR ConclusionsOur study shows that some bacterial species during pregnancy contributed to the onset of prediabetes within two-year postpartum. These were attributable primarily to a lower abundance of short-chain fatty acids-producing bacteria.</p

Aberrations in the early pregnancy serum metabolic profile in women with prediabetes at two years postpartum

IntroductionAberrations in circulating metabolites have been associated with diabetes and cardiovascular risk.ObjectivesTo investigate if early and late pregnancy serum metabolomic profiles differ in women who develop prediabetes by two years postpartum compared to those who remain normoglycemic.MethodsAn NMR metabolomics platform was used to measure 228 serum metabolite variables from women with pre-pregnancy overweight in early and late pregnancy. Co-abundant groups of metabolites were compared between the women who were (n = 40) or were not (n = 138) prediabetic at two years postpartum. Random Forests classifiers, based on the metabolic profiles, were used to predict the prediabetes status, and correlations of the metabolites to glycemic traits (fasting glucose and insulin, HOMA2-IR and HbA1c) and hsCRP at postpartum were evaluated.ResultsWomen with prediabetes had higher concentrations of small HDL particles, total lipids in small HDL, phospholipids in small HDL and free cholesterol in small HDL in early pregnancy (p = 0.029; adj with pre-pregnancy BMI p = 0.094). The small HDL related metabolites also correlated positively with markers of insulin resistance at postpartum. Similar associations were not detected for metabolites in late pregnancy. A Random Forests classifier based on serum metabolites and clinical variables in early pregnancy displayed an acceptable predictive power for the prediabetes status at postpartum (AUROC 0.668).ConclusionElevated serum concentrations of small HDL particles in early pregnancy associate with prediabetes and insulin resistance at two years postpartum. The serum metabolic profile during pregnancy might be used to identify women at increased risk for type 2 diabetes.</p

Perinatal depressive and anxiety symptoms are associated with gut microbiota in pregnant women with overweight and obesity

The associations of gut microbiota with depressive and anxiety symptoms have been investigated mainly in non-pregnant humans, and currently there is a significant gap in research on pregnant women, especially those who are living with overweight and thus at a higher risk for experiencing perinatal mental health problems. In this study, we used shotgun metagenomic sequencing to analyze the gut microbiota of pregnant women with overweight and obesity, both in early and late pregnancy. We compared gut microbial diversity, composition, and function across groups with different trajectories of depressive (n=419) and anxiety (n=408) symptoms. Depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS), and anxiety symptoms were evaluated with the Symptom Checklist 90 (SCL-90, anxiety subscale) at five time points spanning from early pregnancy to one year postpartum. Latent growth mixture modeling (LGMM) was used to model symptom trajectories from early pregnancy until one year postpartum and further symptom sum scores at five time points cross-sectionally. We observed differences in several bacterial species abundances between the trajectory groups and in cross-sectional analyses, including higher abundance of Hungatella hathewayi in the Moderate and increasing depressive symptoms group (FDR<0.25), and Bacteroides clarus in the High and decreasing depressive symptoms group (FDR<0.25) and in women experiencing clinically significant postpartum anxiety symptoms (FDR<0.05). No differences were found regarding the gut microbiota diversity (alpha or beta) or function. The results suggest that maternal gut microbiota, particularly the increased abundance of possible pro-inflammatory species, could be one of the factors affecting perinatal distress

Distinct Diet-Microbiota-Metabolism Interactions in Overweight and Obese Pregnant Women: a Metagenomics Approach

Diet and gut microbiota are known to modulate metabolic health. Our aim was to apply a metagenomics approach to investigate whether the diet-gut microbiota-metabolism and inflammation relationships differ in pregnant overweight and obese women. This cross-sectional study was conducted in overweight (n = 234) and obese (n = 152) women during early pregnancy. Dietary quality was measured by a validated index of diet quality (IDQ). Gut microbiota taxonomic composition and species diversity were assessed by metagenomic profiling (Illumina HiSeq platform). Markers for glucose metabolism (glucose, insulin) and low-grade inflammation (high sensitivity C-reactive protein [hsCRP], glycoprotein acetylation [GlycA]) were analyzed from blood samples. Higher IDQ scores were positively associated with a higher gut microbiota species diversity (r = 0.273, P = 0.007) in obese women, but not in overweight women. Community composition (beta diversity) was associated with the GlycA level in the overweight women (P = 0.04) but not in the obese. Further analysis at the species level revealed a positive association between the abundance of species Alistipes finegoldii and the GlycA level in overweight women (logfold change = 4.74, P = 0.04). This study has been registered at ClinicalTrials.gov under registration no. NCT01922791 (https://clinicaltrials.gov/ct2/show/NCT01922791).</p

Aberrations in the early pregnancy serum metabolic profile in women with prediabetes at two years postpartum

Abstract Introduction Aberrations in circulating metabolites have been associated with diabetes and cardiovascular risk. Objectives To investigate if early and late pregnancy serum metabolomic profiles differ in women who develop prediabetes by two years postpartum compared to those who remain normoglycemic. Methods An NMR metabolomics platform was used to measure 228 serum metabolite variables from women with pre-pregnancy overweight in early and late pregnancy. Co-abundant groups of metabolites were compared between the women who were (n = 40) or were not (n = 138) prediabetic at two years postpartum. Random Forests classifiers, based on the metabolic profiles, were used to predict the prediabetes status, and correlations of the metabolites to glycemic traits (fasting glucose and insulin, HOMA2-IR and HbA1c) and hsCRP at postpartum were evaluated. Results Women with prediabetes had higher concentrations of small HDL particles, total lipids in small HDL, phospholipids in small HDL and free cholesterol in small HDL in early pregnancy (p = 0.029; adj with pre-pregnancy BMI p = 0.094). The small HDL related metabolites also correlated positively with markers of insulin resistance at postpartum. Similar associations were not detected for metabolites in late pregnancy. A Random Forests classifier based on serum metabolites and clinical variables in early pregnancy displayed an acceptable predictive power for the prediabetes status at postpartum (AUROC 0.668). Conclusion Elevated serum concentrations of small HDL particles in early pregnancy associate with prediabetes and insulin resistance at two years postpartum. The serum metabolic profile during pregnancy might be used to identify women at increased risk for type 2 diabetes. </jats:sec

Distinct Diet-Microbiota-Metabolism Interactions in Overweight and Obese Pregnant Women: a Metagenomics Approach

We observed partially distinct diet-gut microbiota-metabolism and inflammation responses in overweight and obese pregnant women. In overweight women, gut microbiota community composition and the relative abundance of A. finegoldii were associated with an inflammatory status. In obese women, a higher dietary quality was related to a higher gut microbiota diversity and a healthy inflammatory status. </jats:p

A distinct gut microbiota composition in pregnant women with perinatal depressive and anxiety symptoms

&lt;p&gt;Source code for the article:&lt;/p&gt; &lt;p&gt;&lt;strong&gt;A distinct gut microbiota composition in pregnant women with perinatal depressive and anxiety symptoms&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Authors: Janina Hieta, Chouaib Benchraka, Katariina P&auml;rn&auml;nen, Noora Houttu, Kati Mokkala, Mrunalini Lotankar, Eeva-Leena Kataja, Leo Lahti, Kirsi Laitinen&lt;/p&gt; &lt;p&gt;Contact: &lt;a href="mailto:[email protected]"&gt;[email protected]&lt;/a&gt;&lt;/p&gt