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© 2016 by The American Society for Biochemistry and Molecular Biology, Inc. Numerous affinity purification-mass spectrometry (APMS) and yeast two-hybrid screens have each defined thousands of pairwise protein-protein interactions (PPIs), most of which are between functionally unrelated proteins. The accuracy of these networks, however, is under debate. Here, we present an AP-MS survey of the bacterium Desulfovibrio vulgaris together with a critical reanalysis of nine published bacterial yeast two-hybrid and AP-MS screens. We have identified 459 high confidence PPIs from D. vulgaris and 391 from Escherichia coli. Compared with the nine published interactomes, our two networks are smaller, are much less highly connected, and have significantly lower false discovery rates. In addition, our interactomes are much more enriched in protein pairs that are encoded in the same operon, have similar functions, and are reproducibly detected in other physical interaction assays than the pairs reported in prior studies. Our work establishes more stringent benchmarks for the properties of protein interactomes and suggests that bona fide PPIs much more frequently involve protein partners that are annotated with similar functions or that can be validated in independent assays than earlier studies suggested.

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram- negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein−protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms.

Norovirus (NoV) GII-4 has emerged as the predominant NoV genotype in outbreaks of gastroenteritis worldwide. We determined clinical features of NoV GII-4 associated acute gastroenteritis (AGE) in comparison with AGE associated with other NoV types in infants during seasons 2001 and 2002. During the prospective follow-up period, 128 primary infections of AGE due to NoV were identified in 405 infants; of these, GII-4 was found in 40 cases (31%). NoV GII-4 was associated with longer duration of diarrhea and vomiting than other NoV genotypes, suggesting greater virulence of NoV GII-4.

We explored whether human rotavirus vaccine had any efficacy against norovirus (NV)-associated gastroenteritis in young children. In an efficacy trial of rotavirus vaccine, 405 infants were immunized with a human rotavirus vaccine or placebo at a ratio of 2:1, and prospectively followed for acute gastroenteritis (AGE) from approximately 2 months to 2 y of age. Multiplex real-time reverse transcription polymerase chain reaction (Mrt RT-PCR) assays were used for detection and quantitation of NVs of genogroup I (GI) and genogroup II (GII) in stool specimens. NVs were detected in 155 (32%) of 485 episodes of AGE. Of these, NV was the only gastroenteritis virus detected in the stools in 142 (29%) episodes. GI and GII NVs were found in 12% and 88% of the cases, respectively. NV as the only gastroenteritis virus was detected in 36% of the infants in the rotavirus vaccine group and 27% in the placebo group. The clinical severity of NV-associated AGE in the vaccine and placebo recipients was not different. NVs were the most common etiologic agents of AGE in children under 2 y of age. Human rotavirus vaccine did not protect against NV gastroenteritis.

Our scheme for the tagless purification of water soluble complexes. 10 g of protein from a crude bacterial extract is first fractionated by ammonium sulfate precipitation and then by a series of chromatographic steps: anion exchange (IEX), hydrophobic interaction (HIC), and finally size exclusion (Gel Filtration). Fractions from the last chromatography step are trypsin digested and peptides labeled with iTRAQ reagents to allow multiplexing and quantitation during mass spectrometric analysis. Elution profiles of identified proteins are then subjected to clustering analysis.