In vitro interaction network of a synthetic gut bacterial community

A key challenge in microbiome research is to predict the functionality of microbial communities based on community membership and (meta)-genomic data. As central microbiota functions are determined by bacterial community networks, it is important to gain insight into the principles that govern bacteria-bacteria interactions. Here, we focused on the growth and metabolic interactions of the Oligo-Mouse-Microbiota (OMM¹²) synthetic bacterial community, which is increasingly used as a model system in gut microbiome research. Using a bottom-up approach, we uncovered the directionality of strain-strain interactions in mono- and pairwise co-culture experiments as well as in community batch culture. Metabolic network reconstruction in combination with metabolomics analysis of bacterial culture supernatants provided insights into the metabolic potential and activity of the individual community members. Thereby, we could show that the OMM¹² interaction network is shaped by both exploitative and interference competition in vitro in nutrient-rich culture media and demonstrate how community structure can be shifted by changing the nutritional environment. In particular, Enterococcus faecalis KB1 was identified as an important driver of community composition by affecting the abundance of several other consortium members in vitro. As a result, this study gives fundamental insight into key drivers and mechanistic basis of the OMM¹² interaction network in vitro, which serves as a knowledge base for future mechanistic in vivo studies.Subject terms: Microbiome, Microbial ecology     

Detection and Enumeration of Fecal Indicator Organisms in Frozen Sea Foods: II. Enterococci

Consistently high recoveries of enterococci as compared to the low numbers of coliforms obtained from the same samples of frozen sea foods are indirect evidence that enterococci are better indicators of contamination in such foods.

The use of azide dextrose broth, modified by the incorporation of bromthymol blue, and of ethyl violet azide broth as presumptive and confirmation tests, respectively, were found to be highly specific for the detection and enumeration of enterococci in these samples. Tetrazolium agar medium, when used as a third step after the confirmation test, provides a reliable differentiation of Streplococcus faecalis types from other group D streptococci. A simple procedure is described for further identification of S. faecalis varieties and other enterococcal species.

Incidence of biotypes within certain species is noted and relationships of these subgroups to the organisms described by other workers is discussed.

The striking resistance of all group D streptococci to dihydrostreptomycin and polymyxin B seems to offer promise for evolving a new selective medium for these organisms.

     

Momordica charantia trypsin inhibitor II inhibits growth and development of Helicoverpa armigera

Abstract  Bitter gourd ( Momordica charantia L.) seeds contain several squash-type serine proteinase inhibitors (PIs), which inhibit the digestive proteinases of the polyphagous insect pest Helicoverpa armigera . In the present work isolation of a DNA sequence encoding the mature peptide of a trypsin inhibitor McTI-II, its cloning and expression as a recombinant protein using Pichia pastoris have been reported. Recombinant McTI-II inhibited bovine trypsin at 1: 1 molar ratio, as expected, but did not inhibit chymotrypsin or elastase. McTI-II also strongly inhibited trypsin-like proteinases (81% inhibition) as well as the total proteolytic activity of digestive proteinases (70% inhibition) from the midgut of H. armigera larvae. The insect larvae fed with McTI-II-incorporated artificial diet suffered over 70% reduction in the average larval weight after 12 days of feeding. Moreover, ingestion of McTI-II resulted in 23% mortality in the larval population. The strong antimetabolic activity of McTI-II toward H. armigera indicates its probable use in developing insect tolerance in susceptible plants.     

fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets

Tools for estimating population structure from genetic data are now used in a wide variety of applications in population genetics. However, inferring population structure in large modern data sets imposes severe computational challenges. Here, we develop efficient algorithms for approximate inference of the model underlying the STRUCTURE program using a variational Bayesian framework. Variational methods pose the problem of computing relevant posterior distributions as an optimization problem, allowing us to build on recent advances in optimization theory to develop fast inference tools. In addition, we propose useful heuristic scores to identify the number of populations represented in a data set and a new hierarchical prior to detect weak population structure in the data. We test the variational algorithms on simulated data and illustrate using genotype data from the CEPH–Human Genome Diversity Panel. The variational algorithms are almost two orders of magnitude faster than STRUCTURE and achieve accuracies comparable to those of ADMIXTURE. Furthermore, our results show that the heuristic scores for choosing model complexity provide a reasonable range of values for the number of populations represented in the data, with minimal bias toward detecting structure when it is very weak. Our algorithm, fastSTRUCTURE, is freely available online at http://pritchardlab.stanford.edu/structure.html.     

Significance of PELP1 in ER-negative breast cancer metastasis

Breast cancer metastasis is a major clinical problem. The molecular basis of breast cancer progression to metastasis remains poorly understood. PELP1 is an estrogen receptor (ER) coregulator that has been implicated as a proto-oncogene whose expression is deregulated in metastatic breast tumors and whose expression is retained in ER-negative tumors. We examined the mechanism and significance of PELP1-mediated signaling in ER-negative breast cancer progression using two ER-negative model cells (MDA-MB-231 and 4T1 cells) that stably express PELP1-shRNA. These model cells had reduced PELP1 expression (75% of endogenous levels) and exhibited less propensity to proliferate in growth assays in vitro. PELP1 downregulation substantially affected migration of ER-negative cells in Boyden chamber and invasion assays. Using mechanistic studies, we found that PELP1 modulated expression of several genes involved in the epithelial mesenchymal transition (EMT), including MMPs, SNAIL, TWIST, and ZEB. In addition, PELP1 knockdown reduced the in vivo metastatic potential of ER-negative breast cancer cells and significantly reduced lung metastatic nodules in a xenograft assay. These results implicate PELP1 as having a role in ER-negative breast cancer metastasis, reveal novel mechanism of coregulator regulation of metastasis via promoting cell motility/EMT by modulating expression of genes, and suggest PELP1 may be a potential therapeutic target for metastatic ER-negative breast cancer.     

Potent antitumor effects of combination therapy with IFNs and monocytes in mouse models of established human ovarian and melanoma tumors

Interferon-activated monocytes are known to exert cytocidal activity against tumor cells in vitro. Here, we have examined whether a combination of IFN-α2a and IFN-γ and human monocytes mediate significant antitumor effects against human ovarian and melanoma tumor xenografts in mouse models. OVCAR-3 tumors were treated i.t. with monocytes alone, IFN-α2a and IFN-γ alone or combination of all three on day 0, 15 or 30 post-tumor implantation. Mice receiving combination therapy beginning day 15 showed significantly reduced tumor growth and prolonged survival including complete regression in 40% mice. Tumor volumes measured on day 80 in mice receiving combination therapy (206 mm(3)) were significantly smaller than those of mice receiving the IFNs alone (1,041 mm(3)), monocytes alone (1,111 mm(3)) or untreated controls (1,728 mm(3)). Similarly, combination therapy with monocytes and IFNs of much larger tumor also inhibited OVCAR-3 tumor growth. Immunohistochemistry studies showed a large number of activated macrophages (CD31(+)/CD68(+)) infiltrating into OVCAR-3 tumors and higher densities of IL-12, IP10 and NOS2, markers of M1 (classical) macrophages in tumors treated with combination therapy compared to the controls. Interestingly, IFNs-activated macrophages induced apoptosis of OVCAR-3 tumor cells as monocytes alone or IFNs alone did not mediate significant apoptosis. Similar antitumor activity was observed in the LOX melanoma mouse model, but not as profound as seen with the OVCAR-3 tumors. Administration of either mixture of monocytes and IFN-α2a or monocytes and IFN-γ did not inhibit Lox melanoma growth; however, a significant inhibition was observed when tumors were treated with a mixture of monocytes, IFN-α2a and IFN-γ. These results indicate that monocytes and both IFN-α2a and IFN-γ may be required to mediate profound antitumor effect against human ovarian and melanoma tumors in mouse models.     

Development of genome-wide SSR markers in horsegram and their use for genetic diversity and cross-transferability analysis

Horsegram [Macrotyloma uniflorum (Lam.) Verdc.] commonly known as kulthi or Madras gram is an important drought tolerant legume crop used as food and fodder in India and across the globe. Horsegram is tolerant to many biotic and abiotic stresses and considered a potential future food legume. Despite being a multiutility crop, insufficient genomic information is available in this species, which is otherwise required for genetic improvement. Hence, in the present work we used next-generation sequencing (NGS) technology for genome-wide development and characterization of novel simple sequence repeat (SSR) markers in horsegram. In all, 2458 SSR primer pairs were designed from NGS data and 117 SSRs were characterized in 48 diverse lines of horsegram. Cross-transferability of these markers was also checked in nine related legume species. The polymorphic SSRs revealed high diversity measures such as mean values of expected heterozygosity (He; 0.54), observed heterozygosity (Ho; 0.64), and polymorphism information content (PIC; 0.46). Analysis of molecular variance (AMOVA) revealed high degree of genetic variance within the populations. Dendrogram based on Jaccard’s similarity coefficient and principal component analysis (PCA) revealed two groups in the analyzed accessions. This observation was further confirmed by Bayesian genetic STRUCTURE analysis. The SSR markers developed herein can be used in diverse genetic analysis including association mapping in this crop and also in related legume crops with limited marker resources. Hence, this new SSR dataset can be useful for molecular breeding research in this underutilized pulse crop. In addition, genetic diversity estimates of analyzed germplasm can be important for devising future breeding programmes in horsegram.