Label-Free Proteomics of a Defined, Binary Co-culture Reveals Diversity of Competitive Responses Between Members of a Model Soil Microbial System.

Interactions among members of microbial consortia drive the complex dynamics in soil, gut, and biotechnology microbiomes. Proteomic analysis of defined co-cultures of well-characterized species provides valuable information about microbial interactions. We used a label-free approach to quantify the responses to co-culture of two model bacterial species relevant to soil and rhizosphere ecology, Bacillus atrophaeus and Pseudomonas putida. Experiments determined the ratio of species in co-culture that would result in the greatest number of high-confidence protein identifications for both species. The 281 and 256 proteins with significant shifts in abundance for B. atrophaeus and P. putida, respectively, indicated responses to co-culture in overall metabolism, cell motility, and response to antagonistic compounds. Proteins associated with a virulent phenotype during surface-associated growth were significantly more abundant for P. putida in co-culture. Co-culture on agar plates triggered a filamentous phenotype in P. putida and avoidance of P. putida by B. atrophaeus colonies, corroborating antagonistic interactions between these species. Additional experiments showing increased relative abundance of P. putida under conditions of iron or zinc limitation and increased relative abundance of B. atrophaeus under magnesium limitation were consistent with patterns of changes in abundance of metal-binding proteins during co-culture. These results provide details on the nature of interactions between two species with antagonistic capabilities. Significant challenges remaining for the development of proteomics as a tool in microbial ecology include accurate quantification of low-abundance peptides, especially from rare species present at low relative abundance in a consortium.

Characterization of the relative importance of human- and infrastructure-associated bacteria in grey water: a case study.

AIMS: Development of efficacious grey water (GW) treatment systems would benefit from detailed knowledge of the bacterial composition of GW. Thus, the aim of this study was to characterize the bacterial composition from (i) various points throughout a GW recycling system that collects shower and sink handwash (SH) water into an equalization tank (ET) prior to treatment and (ii) laundry (LA) water effluent of a commercial-scale washer. METHODS AND RESULTS: Bacterial composition was analysed by high-throughput pyrosequencing of the 16S rRNA gene. LA was dominated by skin-associated bacteria, with Corynebacterium, Staphylococcus, Micrococcus, Propionibacterium and Lactobacillus collectively accounting for nearly 50% of the total sequences. SH contained a more evenly distributed community than LA, with some overlap (e.g. Propionibacterium), but also contained distinct genera common to wastewater infrastructure (e.g. Zoogloea). The ET contained many of these same wastewater infrastructure-associated bacteria, but was dominated by genera adapted for anaerobic conditions. CONCLUSIONS: The data indicate that a relatively consistent set of skin-associated genera are the dominant human-associated bacteria in GW, but infrastructure-associated bacteria from the GW collection system and ET used for transient storage will be the most common bacteria entering GW treatment and reuse systems. SIGNIFICANCE AND IMPACT OF THE STUDY: This study is the first to use high-throughput sequencing to identify the bacterial composition of various GW sources.

Quantification of genes and gene transcripts for microbial perchlorate reduction in fixed-bed bioreactors.

AIMS: Optimization of full-scale, biological perchlorate treatment processes for drinking water would benefit from knowledge of the location and quantity of perchlorate-reducing bacteria (PRB) and expression of perchlorate-related genes in bioreactors. The aim of this study was to quantify perchlorate removal and perchlorate-related genes (pcrA and cld) and their transcripts in bioreactors and to determine whether these genes or transcripts could serve as useful biomarkers for perchlorate treatment processes. METHODS AND RESULTS: Quantitative PCR (qPCR) assays targeting pcrA and cld were applied to two pilot-scale, fixed-bed bioreactors treating perchlorate-contaminated groundwater. pcrA and cld genes per microgram of DNA were two- to threefold higher and three- to fourfold higher, respectively, in the bioreactor showing superior perchlorate-removal performance. In a laboratory-scale bioreactor, quantities of pcrA and cld genes and transcripts were compared under two distinct performance conditions (c.60 and 20% perchlorate removal) for a 5-min empty bed contact time. cld genes per microgram of DNA were approximately threefold higher and cld transcripts per microgram of RNA were approximately sixfold higher under the higher perchlorate-removal condition. No differences in pcrA genes or transcripts per microgram of DNA or RNA, respectively, were detected between the c.60 and 20% perchlorate-removal conditions, possibly because these assays did not accurately quantify pcrA genes and transcripts in the mixed culture present. CONCLUSIONS: Quantities of cld genes and transcripts per microgram of DNA and RNA, respectively, were found to be higher when perchlorate removal was higher. However, quantities of pcrA and cld genes or transcripts were not found to directly correlate with perchlorate-removal rates. SIGNIFICANCE AND IMPACT OF THE STUDY: To our knowledge, this study represents the first application of qPCR assays to quantify perchlorate-related genes and transcripts in continuous-flow bioreactors. The results indicate that cld gene and transcript quantities can provide insights regarding the quantity, location and gene expression of PRB in bioreactors.

Loss of translational control in yeast compromised for the major mRNA decay pathway.

The cytoplasmic fate of mRNAs is dictated by the relative activities of the intimately connected mRNA decay and translation initiation pathways. In this study, we have found that yeast strains compromised for stages downstream of deadenylation in the major mRNA decay pathway are incapable of inhibiting global translation initiation in response to stress. In the past, the paradigm of the eIF2alpha kinase-dependent amino acid starvation pathway in yeast has been used to evaluate this highly conserved stress response in all eukaryotic cells. Using a similar approach we have found that even though the mRNA decay mutants maintain high levels of general translation, they exhibit many of the hallmarks of amino acid starvation, including increased eIF2alpha phosphorylation and activated GCN4 mRNA translation. Therefore, these mutants appear translationally oblivious to decreased ternary complex abundance, and we propose that this is due to higher rates of mRNA recruitment to the 40S ribosomal subunit.

A novel eIF2B-dependent mechanism of translational control in yeast as a response to fusel alcohols.

Fusel alcohols are natural products of amino acid catabolism in the yeast Saccharomyces cerevisiae that cause morphological changes similar to those seen during pseudohyphal growth. We have discovered that certain of these alcohols, including butanol and isoamyl alcohol, bring about a rapid inhibition of translation at the initiation step. This inhibition is strain specific and is not explained by previously described translational control pathways. Using genetic mapping, we have identified a proline to serine allelic variation at amino acid 180 of the GCD1 gene product as the genetic locus that allows translational regulation upon butanol addition. Gcd1p forms part of the eIF2B guanine nucleotide complex that is responsible for recycling eIF2-GDP to eIF2-GTP. This represents one of the key limiting steps of translation initiation and we provide evidence that fusel alcohols target eIF2B in order to bring about translational regulation.

Glucose depletion rapidly inhibits translation initiation in yeast.

Glucose performs key functions as a signaling molecule in the yeast Saccharomyces cerevisiae. Glucose depletion is known to regulate gene expression via pathways that lead to derepression of genes at the transcriptional level. In this study, we have investigated the effect of glucose depletion on protein synthesis. We discovered that glucose withdrawal from the growth medium led to a rapid inhibition of protein synthesis and that this effect was readily reversed upon readdition of glucose. Neither the inhibition nor the reactivation of translation required new transcription. This inhibition also did not require activation of the amino acid starvation pathway or inactivation of the TOR kinase pathway. However, mutants in the glucose repression (reg1, glc7, hxk2, and ssn6), hexose transporter induction (snf3 rgt2), and cAMP-dependent protein kinase (tpk1(w) and tpk2(w)) pathways were resistant to the inhibitory effects of glucose withdrawal on translation. These findings highlight the intimate connection between the nutrient status of the cell and its translational capacity. They also help to define a new area of posttranscriptional regulation in yeast.