Project description:Mitochondrial rRNAs play important roles in regulating mtDNA-encoded gene expression and energy metabolism subsequently. However, the proteins that regulate mitochondrial 16S rRNA processing remain poorly understood. Herein, we generated adipose-specific Wbscr16-/- mice and cells, both of which exhibited dramatic mitochondrial changes. Subsequently, WBSCR16 was identified as a 16S rRNA-binding protein essential for the cleavage of 16S rRNA-mt-tRNALeu, facilitating 16S rRNA processing and mitochondrial ribosome assembly. Additionally, WBSCR16 recruited RNase P subunit MRPP3 to nascent 16S rRNA and assisted in this specific cleavage. Furthermore, evidence showed that adipose-specific Wbscr16 ablation promotes energy wasting via lipid preference in brown adipose tissue, leading to excess energy expenditure and resistance to obesity. In contrast, overexpression of WBSCR16 upregulated 16S rRNA processing and induced a preference for glucose utilization in both transgenic mouse models and cultured cells. These findings suggest that WBSCR16 plays essential roles in mitochondrial 16S rRNA processing in mammals, and is the key mitochondrial protein to balance glucose and lipid metabolism.
Project description:An Easy Operating Pathogen Microarray (EOPM) was designed to detect almost all known pathogens and related species based on their genomic sequences. For effective identification of pathogens from EOPM data, a statistical enrichment algorithm has been proposed and further implemented in a user-friendly interface. A microarray was designed with probes for vertebrate-infecting virus sequences in EMBL, 18S rRNA fungi and parasite sequences from EMBL, and 16S rRNA sequences of bacteria from RDP, synthesized on the Agilent platform. The array was tested using 2 color dyes on cultured microbes and on clinical samples from sick and healthy people, looking for differences in clinically ill people compared to a number of healthy "controls".
Project description:This study aimed to model formamide-based melting for the optimization of the sensitivity and specifcity of oligonucleotide probes in dignostic high-density microarrays. Formamide melting profiles of DNA oligonucleotides were obtained with a high-density microarray targeting 16S rRNA genes of Escherichia coli and Rhodobacter sphaeroides. One or two mismatched versions of perfect match probes were included on the array to systematically analyze the effect of formamide on mismatch stability and mismatch discrimination. A thermodynamics-based mathematical model of formamide denaturation was developed to predict the formamide melting profiles with sufficient accuracy to help with oligonucleotide design in microbial ecology applications. 16S rRNA sequences with GenBank accession codes U00006 ( E. coli ) and X53853 (R. sphaeroides) were used for probe design. The following oligonucleotide probe sets were used for the systematic analysis of the effect of formamide on probe-target hybrids (parenthetic information gives set name followed by the number of probes): 22-mer perfect match probes tiling the 16S rRNA gene of E. coli (TileE, n=1521), perfect match E.coli probes of variable length between 18 and 26 mers (Length, n=1045), E. coli probes with central single mismatches (OneM, n=1563), E. coli probes with single positional mismatches (PosM, n=4092), E. coli probes with single deletion mismatches (Gap, n=248), E. coli probes with single insertion mismatches (Insertion, n=248), E. coli probes with two separate mismatches (TwoM, n=1674), E. coli probes with central tandem mismatches (Tandem, n=558), and 22-mer perfect match probes tiling the 16S rRNA gene of R. sphaeroides. Also, a probe with no match to 16S rRNA genes was used as a background control. On the array, regular probes were replicated three times and the Nonsense probe ten times. See the manuscript of Yilmaz et al. for details.
Project description:To effectively monitor microbial populations in acidic environments and bioleaching systems, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the known genes associated with the acidophiles. This array contained 1,072 probes in which there were 571 related to 16S rRNA and 501 related to functional genes. Acid mine drainage (AMD) presents numerous problems to the aquatic life and surrounding ecosystems. However, little is known about the geographic distribution, diversity, composition, structure and function of AMD microbial communities. In this study, we analyzed the geographic distribution of AMD microbial communities from twenty sites using restriction fragment length polymorphism (RFLP) analysis of 16S rRNA genes, and the results showed that AMD microbial communities were geographically distributed and had high variations among different sites. Then an AMD-specific microarray was used to further analyze nine AMD microbial communities, and showed that those nine AMD microbial communities had high variations measured by the number of detected genes, overlapping genes between samples, unique genes, and diversity indices. Statistical analyses indicated that the concentrations of Fe, S, Ca, Mg, Zn, Cu and pH had strong impacts on both phylogenetic and functional diversity, composition, and structure of AMD microbial communities. This study provides insights into our understanding of the geographic distribution, diversity, composition, structure and functional potential of AMD microbial communities and key environmental factors shaping them. This study investigated the geographic distribution of Acid Mine Drainages microbial communities using a 16S rRNA gene-based RFLP method and the diversity, composition and structure of AMD microbial communities phylogenetically and functionally using an AMD-specific microarray which contained 1,072 probes ( 571 related to 16S rRNA and 501 related to functional genes). The functional genes in the microarray were involved in carbon metabolism (158), nitrogen metabolism (72), sulfur metabolism (39), iron metabolism (68), DNA replication and repair (97), metal-resistance (27), membrane-relate gene (16), transposon (13) and IST sequence (11).