TlpC, a novel chemotaxis protein in Rhodobacter sphaeroides , localizes to a discrete region in the cytoplasm

TlpC is encoded in the second chemotaxis operon of Rhodobacter sphaeroides . This protein shows some homology to membrane-spanning chemoreceptors of many bacterial species but, unlike these, is essential for R. sphaeroides chemotaxis to all compounds tested. Genomic replacement of tlpC with a C-terminal gfp fusion demonstrated that TlpC localized to a discrete cluster within the cytoplasm. Immunogold electron microscopy also showed that TlpC localized to a cytoplasmic electron-dense region. Correct TlpC–GFP localization depended on the downstream signalling proteins, CheW 3 , CheW 4 and CheA 2 , and was tightly linked to cell division. Newly divided cells contained a single cluster but, as the cell cycle progressed, a second cluster appeared close to the initial cluster. As elongation continued, these clusters moved apart so that, on septation, each daughter cell contained a single TlpC cluster. The data presented suggest that TlpC is either a cytoplasmic chemoreceptor responding to or integrating global signals of metabolic state or a novel and essential component of the chemotaxis signalling pathway. These data also suggest that clustering is essential for signalling and that a mechanism may exist for targeting and localizing proteins within the bacterial cytoplasm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75441/1/j.1365-2958.2002.03252.x.pd

Discerning Tumor Status from Unstructured MRI Reports—Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing

Information in electronic medical records is often in an unstructured free-text format. This format presents challenges for expedient data retrieval and may fail to convey important findings. Natural language processing (NLP) is an emerging technique for rapid and efficient clinical data retrieval. While proven in disease detection, the utility of NLP in discerning disease progression from free-text reports is untested. We aimed to (1) assess whether unstructured radiology reports contained sufficient information for tumor status classification; (2) develop an NLP-based data extraction tool to determine tumor status from unstructured reports; and (3) compare NLP and human tumor status classification outcomes. Consecutive follow-up brain tumor magnetic resonance imaging reports (2000–­2007) from a tertiary center were manually annotated using consensus guidelines on tumor status. Reports were randomized to NLP training (70%) or testing (30%) groups. The NLP tool utilized a support vector machines model with statistical and rule-based outcomes. Most reports had sufficient information for tumor status classification, although 0.8% did not describe status despite reference to prior examinations. Tumor size was unreported in 68.7% of documents, while 50.3% lacked data on change magnitude when there was detectable progression or regression. Using retrospective human classification as the gold standard, NLP achieved 80.6% sensitivity and 91.6% specificity for tumor status determination (mean positive predictive value, 82.4%; negative predictive value, 92.0%). In conclusion, most reports contained sufficient information for tumor status determination, though variable features were used to describe status. NLP demonstrated good accuracy for tumor status classification and may have novel application for automated disease status classification from electronic databases

Multiple evolutionary origins of Trypanosoma evansi in Kenya

Trypanosoma evansi is the parasite causing surra, a form of trypanosomiasis in camels and other livestock, and a serious economic burden in Kenya and many other parts of the world. Trypanosoma evansi transmission can be sustained mechanically by tabanid and Stomoxys biting flies, whereas the closely related African trypanosomes T. brucei brucei and T. b. rhodesiense require cyclical development in tsetse flies (genus Glossina) for transmission. In this study, we investigated the evolutionary origins of T. evansi. We used 15 polymorphic microsatellites to quantify levels and patterns of genetic diversity among 41 T. evansi isolates and 66 isolates of T. b. brucei (n = 51) and T. b. rhodesiense (n = 15), including many from Kenya, a region where T. evansi may have evolved from T. brucei. We found that T. evansi strains belong to at least two distinct T. brucei genetic units and contain genetic diversity that is similar to that in T. brucei strains. Results indicated that the 41 T. evansi isolates originated from multiple T. brucei strains from different genetic backgrounds, implying independent origins of T. evansi from T. brucei strains. This surprising finding further suggested that the acquisition of the ability of T. evansi to be transmitted mechanically, and thus the ability to escape the obligate link with the African tsetse fly vector, has occurred repeatedly. These findings, if confirmed, have epidemiological implications, as T. brucei strains from different genetic backgrounds can become either causative agents of a dangerous, cosmopolitan livestock disease or of a lethal human disease, like for T. b. rhodesiense

A Meta-Analysis of Probiotic Efficacy for Gastrointestinal Diseases

Background: Meta-analyses on the effects of probiotics on specific gastrointestinal diseases have generally shown positive effects on disease prevention and treatment; however, the relative efficacy of probiotic use for treatment and prevention across different gastrointestinal diseases, with differing etiology and mechanisms of action, has not been addressed. Methods/Principal Findings: We included randomized controlled trials in humans that used a specified probiotic in the treatment or prevention of Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, Antibiotic Associated Diarrhea, Traveler’s Diarrhea, or Necrotizing Enterocolitis. Random effects models were used to evaluate efficacy as pooled relative risks across the eight diseases as well as across probiotic species, single vs. multiple species, patient ages, dosages, and length of treatment. Probiotics had a positive significant effect across all eight gastrointestinal diseases with a relative risk of 0.58 (95 % (CI) 0.51–0.65). Six of the eight diseases: Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, and Antibiotic Associated Diarrhea, showed positive significant effects. Traveler’s Diarrhea and Necrotizing Enterocolitis did not show significant effects of probiotcs. Of the 11 species and species mixtures, all showed positive significant effects except for Lactobacillus acidophilus, Lactobacillus plantarum, and Bifidobacterium infantis. Across all diseases and probiotic species, positive significant effects of probiotics were observed for all age groups, single vs. multiple species, and treatment lengths

Genome of <i>Leptomonas pyrrhocoris</i>:a high-quality reference for monoxenous trypanosomatids and new insights into evolution of <i>Leishmania</i>

Many high-quality genomes are available for dixenous (two hosts) trypanosomatid species of the genera Trypanosoma, Leishmania, and Phytomonas, but only fragmentary information is available for monoxenous (single-host) trypanosomatids. In trypanosomatids, monoxeny is ancestral to dixeny, thus it is anticipated that the genome sequences of the key monoxenous parasites will be instrumental for both understanding the origin of parasitism and the evolution of dixeny. Here, we present a high-quality genome for Leptomonas pyrrhocoris, which is closely related to the dixenous genus Leishmania. The L. pyrrhocoris genome (30.4 Mbp in 60 scaffolds) encodes 10,148 genes. Using the L. pyrrhocoris genome, we pinpointed genes gained in Leishmania. Among those genes, 20 genes with unknown function had expression patterns in the Leishmania mexicana life cycle suggesting their involvement in virulence. By combining differential expression data for L. mexicana, L. major and Leptomonas seymouri, we have identified several additional proteins potentially involved in virulence, including SpoU methylase and U3 small nucleolar ribonucleoprotein IMP3. The population genetics of L. pyrrhocoris was also addressed by sequencing thirteen strains of different geographic origin, allowing the identification of 1,318 genes under positive selection. This set of genes was significantly enriched in components of the cytoskeleton and the flagellum

Reconstruction of the Core and Extended Regulons of Global Transcription Factors

The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual α-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the α-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks