Metabolomics provide new insights into mechanisms of Wolbachia-induced paternal defects in Drosophila melanogaster

Wolbachia is a group of intracellular symbiotic bacteria that widely infect arthropods and nematodes. Wolbachia infection can regulate host reproduction with the most common phenotype in insects being cytoplasmic incompatibility (CI), which results in embryonic lethality when uninfected eggs fertilized with sperms from infected males. This suggests that CI-induced defects are mainly in paternal side. However, whether Wolbachia-induced metabolic changes play a role in the mechanism of paternal-linked defects in embryonic development is not known. In the current study, we first use untargeted metabolomics method with LC-MS to explore how Wolbachia infection influences the metabolite profiling of the insect hosts. The untargeted metabolomics revealed 414 potential differential metabolites between Wolbachia-infected and uninfected 1-day-old (1d) male flies. Most of the differential metabolites were significantly up-regulated due to Wolbachia infection. Thirty-four metabolic pathways such as carbohydrate, lipid and amino acid, and vitamin and cofactor metabolism were affected by Wolbachia infection. Then, we applied targeted metabolomics analysis with GC-MS and showed that Wolbachia infection resulted in an increased energy expenditure of the host by regulating glycometabolism and fatty acid catabolism, which was compensated by increased food uptake. Furthermore, overexpressing two acyl-CoA catabolism related genes, Dbi (coding for diazepam-binding inhibitor) or Mcad (coding for medium-chain acyl-CoA dehydrogenase), ubiquitously or specially in testes caused significantly decreased paternal-effect egg hatch rate. Oxidative stress and abnormal mitochondria induced by Wolbachia infection disrupted the formation of sperm nebenkern. These findings provide new insights into mechanisms of Wolbachia-induced paternal defects from metabolic phenotypes.

Distinctiveness of genes contributing to growth of Pseudomonas syringae in diverse host plant species

A variety of traits are necessary for bacterial colonization of the interior of plant hosts, including well-studied virulence effectors as well as other phenotypes contributing to bacterial growth and survival within the apoplast. High-throughput methods such as transposon sequencing (TnSeq) are powerful tools to identify such genes in bacterial pathogens. However, there is little information as to the distinctiveness of traits required for bacterial colonization of different hosts. Here, we utilize randomly barcoded TnSeq (RB-TnSeq) to identify the genes that contribute to the ability of Pseudomonas syringae strain B728a to grow within common bean (Phaseolus vulgaris), lima bean (Phaseolus lunatus), and pepper (Capsicum annuum); species representing two different plant families. The magnitude of contribution of most genes to apoplastic fitness in each of the plant hosts was similar. However, 50 genes significantly differed in their fitness contributions to growth within these species. These genes encoded proteins in various functional categories including polysaccharide synthesis and transport, amino acid metabolism and transport, cofactor metabolism, and phytotoxin synthesis and transport. Six genes that encoded unannotated, hypothetical proteins also contributed differentially to growth in these hosts. The genetic repertoire of a relatively promiscuous pathogen such as P. syringae may thus be shaped, at least in part, by the conditional contribution of some fitness determinants.

Coenzyme and cofactor metabolism belongs to biochemical processes significantly regulated in human granulosa cells collected after IVF during long-term primary in vitro culture

Granulosa cells (GCs) provide the microenvironment necessary for the development of the follicle and the maturation of the oocyte. GCs are associated with reproductive system function and the maintenance of pregnancy by participating in the synthesis of steroid hormones. Many authors point to new ways of using GCs in regenerative medicine and indicate the significant plasticity of this cell population, suggesting that GCs can undergo a transdifferentiation process. Employing primary in vitro cell cultures and high-throughput transcriptome analysis via Affymetrix microarrays, this study describes groups of genes associated with enzymatic reactions. 52 genes were identified belonging to four gene ontology biological process terms (GO BP): “coenzyme biosynthetic process”, “coenzyme metabolic process”, “cofactor biosynthetic process” and “cofactor metabolic process”. All identified genes showed reduction in the level of mRNA expression during long-term in vitro cultivation. Significanthe transcriptomic profile variability was exhibited for the genes (ELOVL5, ELOVL6 and GPAM) involved in enzymatic regulation of fatty acid metabolism.Running title: Enzymatic regulation in granulosa cells

Analysis of the hibernation cycle using LC-MS-based metabolomics in ground squirrel liver

A hallmark of hibernation in mammals is metabolic flexibility, which is typified by reversible bouts of metabolic depression (torpor) and the seasonal shift from predominantly carbohydrate to lipid metabolism from summer to winter. To provide new insight into the control and consequences of hibernation, we used LC/MS-based metabolomics to measure differences in small molecules in ground squirrel liver in five activity states: summer, entering torpor, late torpor, arousing from torpor, and interbout arousal. There were significant alterations both seasonally and within torpor-arousal cycles in enzyme cofactor metabolism, amino acid catabolism, and purine and pyrimidine metabolism, with observed metabolites reduced during torpor and increased upon arousal. Multiple lipids also changed, including 1-oleoyllysophosphatidylcholine, cholesterol sulfate, and sphingosine, which tended to be lowest during torpor, and hexadecanedioic acid, which accumulated during a torpor bout. The results reveal the dramatic alterations that occur in several classes of metabolites, highlighting the value of metabolomic analyses in deciphering the hibernation phenotype.