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Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25–0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales. [ABSTRACT FROM AUTHOR]

Summary Production of chemicals in microbes often employs potent biosynthetic enzymes, which can interact with the microbial native metabolism to affect cell fitness and product yield. However, production optimization largely relies on data collected from wild-type strains in the absence of metabolic perturbations, thus limiting their relevance to specific conditions. Here, we address this issue by coupling cell fitness to the production of thiamine diphosphate in Escherichia coli using a synthetic RNA biosensor. We use this strategy to interrogate a library of transposon mutants and elucidate the native gene network influencing both cell fitness and thiamine production. Ultimately, we identify effectors of the OxyR-Fur stress response that limit thiamine biosynthesis via alternative regulation of iron storage and Fe-S cluster inclusion in enzymes. This study presents a new approach for the reliable high-throughput identification of genetic targets of both known and unknown function that are directly relevant to a specific biosynthetic process. [ABSTRACT FROM AUTHOR]

Summary: Predictable operation of engineered biological circuitry requires the knowledge of host factors that compete or interfere with designed function. Here, we perform a detailed analysis of the interaction between constitutive expression from a test circuit and cell-growth properties in a subset of genetic variants of the bacterium Escherichia coli. Differences in generic cellular parameters such as ribosome availability and growth rate are the main determinants (89%) of strain-specific differences of circuit performance in laboratory-adapted strains but are responsible for only 35% of expression variation across 88 mutants of E. coli BW25113. In the latter strains, we identify specific cell functions, such as nitrogen metabolism, that directly modulate circuit behavior. Finally, we expose aspects of carbon metabolism that act in a strain- and sequence-specific manner. This method of dissecting interactions between host factors and heterologous circuits enables the discovery of mechanisms of interference necessary for the development of design principles for predictable cellular engineering. [Copyright &y& Elsevier]

Summary: We have used a human artificial chromosome (HAC) to manipulate the epigenetic state of chromatin within an active kinetochore. The HAC has a dimeric α-satellite repeat containing one natural monomer with a CENP-B binding site, and one completely artificial synthetic monomer with the CENP-B box replaced by a tetracycline operator (tetO). This HAC exhibits normal kinetochore protein composition and mitotic stability. Targeting of several tet-repressor (tetR) fusions into the centromere had no effect on kinetochore function. However, altering the chromatin state to a more open configuration with the tTA transcriptional activator or to a more closed state with the tTS transcription silencer caused missegregation and loss of the HAC. tTS binding caused the loss of CENP-A, CENP-B, CENP-C, and H3K4me2 from the centromere accompanied by an accumulation of histone H3K9me3. Our results reveal that a dynamic balance between centromeric chromatin and heterochromatin is essential for vertebrate kinetochore activity. [Copyright &y& Elsevier]

Cleavage factor Im (CF Im) is required for the first step in pre-mRNA 3′-end processing and can be reconstituted in vitro from its heterologously expressed 25- and 68- kDa subunits. The binding of CF Im to the pre-mRNA is one of the earliest steps in the assembly of the cleavage and polyadenylation machinery and facilitates the recruitment of other processing factors. We identified regions in the subunits of CF Im involved in RNA binding, protein-protein interactions, and subcellular localization. CF Im68 has a modular domain organization consisting of an N-terminal RNA recognition motif and a C-terminal alternating charge domain. However, the RNA recognition motif of CF Im68 on its own is not sufficient to bind RNA but is necessary for association with the 25-kDa subunit. RNA binding appears to require a CF Im68/25 heterodimer. Whereas multiple protein interactions with other 3′-end-processing factors are detected with CF Im25, CF Im68 interacts with SRp20, 9G8, and hTra2β, members of the SR family of splicing factors, via its C-terminal alternating charge domain. This domain is also required for targeting CF Im68 to the nucleus. However, CF Im68 does not concentrate in splicing speckles but in foci that partially colocalize with paraspeckles, a subnuclear component in which other proteins involved in transcriptional control and RNA processing have been found. [ABSTRACT FROM AUTHOR]

Survivin is a key cellular protein thought to function in apoptotic regulation, mitotic progression, or possibly both. In this study, we describe the isolation of two conditional knockouts of the survivin gene in chicken DT40 cells. DT40 cells lacking Survivin die in interphase after failing to complete cytokinesis. However, these cells show normal sensitivity to the chemotherapeutic agent etoposide. Expression of Survivin mutants against a null background to reassess the role of several key residues reveals that DT40 cells can grow normally if their sole Survivin is missing a widely studied cyclin-dependent kinase phosphorylation site or sites reportedly essential for binding to Smac or aurora B. Mutations in the nuclear export sequence or dimerization interface render cells temperature sensitive for growth. As an important caveat for other studies in which protein function is studied by transient transfection, three of the Survivin mutants fail to localize in the presence of the wild-type protein but do localize and indeed support life in its absence. [ABSTRACT FROM AUTHOR]

Export of mRNA from the nucleus is linked to proper processing and packaging into ribonucleoprotein complexes. Although several observations indicate a coupling between mRNA 3' end formation and export, it is not known how these two processes are mechanistically connected. Here, we show that a subunit of the mammalian pre-mRNA 3' end processing complex, CF I(m)68, stimulates mRNA export. CF I(m)68 shuttles between the nucleus and the cytoplasm in a transcription-dependent manner and interacts with the mRNA export receptor NXF1/TAP. Consistent with the idea that CF I(m)68 may act as a novel adaptor for NXF1/TAP, we show that CF I(m)68 promotes the export of a reporter mRNA as well as of endogenous mRNAs, whereas silencing by RNAi results in the accumulation of mRNAs in the nucleus. Moreover, CF I(m)68 associates with 80S ribosomes but not polysomes, suggesting that it is part of the mRNP that is remodeled in the cytoplasm during the initial stages of translation. These results reveal a novel function for the pre-mRNA 3' end processing factor CF I(m)68 in mRNA export.

We previously used a human artificial chromosome (HAC) with a synthetic kinetochore that could be targeted with chromatin modifiers fused to tetracycline repressor to show that targeting of the transcriptional repressor tTS within kinetochore chromatin disrupts kinetochore structure and function. Here we show that the transcriptional corepressor KAP1, a downstream effector of the tTS, can also inactivate the kinetochore. The disruption of kinetochore structure by KAP1 subdomains does not simply result from loss of centromeric CENP-A nucleosomes. Instead it reflects a hierarchical disruption of the outer kinetochore, with CENP-C levels falling before CENP-A levels and, in certain instances, CENP-H being lost more readily than CENP-C. These results suggest that this novel approach to kinetochore dissection may reveal new patterns of protein interactions within the kinetochore.

Mammalian cleavage factor I (CF Im) is an essential factor that is required for the first step in pre-mRNA 3' end processing. Here, we characterize CF Im68 subnuclear distribution and mobility. Fluorescence microscopy reveals that in addition to paraspeckles CF Im68 accumulates in structures that partially overlap with nuclear speckles. Analysis of synchronized cells shows that CF Im68 distribution in speckles and paraspeckles varies during the cell cycle. At an ultrastructural level, CF Im68 is associated with perichromatin fibrils, the sites of active transcription, and concentrates in interchromatin granules-associated zones. We show that CFIm68 colocalizes with bromouridine, RNA polymerase II, and the splicing factor SC35. On inhibition of transcription, endogenous CF Im68 no longer associates with perichromatin fibrils, but it can still be detected in interchromatin granules-associated zones. These observations support the idea that not only splicing but also 3' end processing occurs cotranscriptionally. Finally, fluorescence recovery after photobleaching analysis reveals that the CF Im68 fraction associated with paraspeckles moves at a rate similar to the more dispersed molecules in the nucleoplasm, demonstrating the dynamic nature of this compartment. These findings suggest that paraspeckles are a functional compartment involved in RNA metabolism in the cell nucleus.

Cleavage factor I(m) (CF I(m)) is required for the first step in pre-mRNA 3'-end processing and can be reconstituted in vitro from its heterologously expressed 25- and 68-kDa subunits. The binding of CF I(m) to the pre-mRNA is one of the earliest steps in the assembly of the cleavage and polyadenylation machinery and facilitates the recruitment of other processing factors. We identified regions in the subunits of CF I(m) involved in RNA binding, protein-protein interactions, and subcellular localization. CF I(m)68 has a modular domain organization consisting of an N-terminal RNA recognition motif and a C-terminal alternating charge domain. However, the RNA recognition motif of CF I(m)68 on its own is not sufficient to bind RNA but is necessary for association with the 25-kDa subunit. RNA binding appears to require a CF I(m)68/25 heterodimer. Whereas multiple protein interactions with other 3'-end-processing factors are detected with CF I(m)25, CF I(m)68 interacts with SRp20, 9G8, and hTra2beta, members of the SR family of splicing factors, via its C-terminal alternating charge domain. This domain is also required for targeting CF I(m)68 to the nucleus. However, CF I(m)68 does not concentrate in splicing speckles but in foci that partially colocalize with paraspeckles, a subnuclear component in which other proteins involved in transcriptional control and RNA processing have been found.