The enzymes of bacterial census and censorship.
Ontology highlight
ABSTRACT:
SUBMITTER: Fast W
PROVIDER: S-EPMC3259214 | biostudies-literature | 2012 Jan
REPOSITORIES: biostudies-literature
Publications
The enzymes of bacterial census and censorship.
Fast Walter W Tipton Peter A PA
Trends in biochemical sciences 20111116 1
N-Acyl-L-homoserine lactones (AHLs) are a major class of quorum-sensing signals used by Gram-negative bacteria to regulate gene expression in a population-dependent manner, thereby enabling group behavior. Enzymes capable of generating and catabolizing AHL signals are of significant interest for the study of microbial ecology and quorum-sensing pathways, for understanding the systems that bacteria have evolved to interact with small-molecule signals, and for their possible use in therapeutic and ...[more]
Similar Datasets
Project description:UnlabelledA census is typically carried out for people across a range of geographical levels; however, microbial ecologists have implemented a molecular census of bacteria and archaea by sequencing their 16S rRNA genes. We assessed how well the census of full-length 16S rRNA gene sequences is proceeding in the context of recent advances in high-throughput sequencing technologies because full-length sequences are typically used as references for classification of the short sequences generated by newer technologies. Among the 1,411,234 and 53,546 full-length bacterial and archaeal sequences, 94.5% and 95.1% of the bacterial and archaeal sequences, respectively, belonged to operational taxonomic units (OTUs) that have been observed more than once. Although these metrics suggest that the census is approaching completion, 29.2% of the bacterial and 38.5% of the archaeal OTUs have been observed more than once. Thus, there is still considerable diversity to be explored. Unfortunately, the rate of new full-length sequences has been declining, and new sequences are primarily being deposited by a small number of studies. Furthermore, sequences from soil and aquatic environments, which are known to be rich in bacterial diversity, represent only 7.8 and 16.5% of the census, while sequences associated with host-associated environments represent 55.0% of the census. Continued use of traditional approaches and new technologies such as single-cell genomics and short-read assembly are likely to improve our ability to sample rare OTUs if it is possible to overcome this sampling bias. The success of ongoing efforts to use short-read sequencing to characterize archaeal and bacterial communities requires that researchers strive to expand the depth and breadth of this census.ImportanceThe biodiversity contained within the bacterial and archaeal domains dwarfs that of the eukaryotes, and the services these organisms provide to the biosphere are critical. Surprisingly, we have done a relatively poor job of formally tracking the quality of the biodiversity as represented in full-length 16S rRNA genes. By understanding how this census is proceeding, it is possible to suggest the best allocation of resources for advancing the census. We found that the ongoing effort has done an excellent job of sampling the most abundant organisms but struggles to sample the rarer organisms. Through the use of new sequencing technologies, we should be able to obtain full-length sequences from these rare organisms. Furthermore, we suggest that by allocating more resources to sampling environments known to have the greatest biodiversity, we will be able to make significant advances in our characterization of archaeal and bacterial diversity.
| S-EPMC4895100 | biostudies-literature
Project description:The global diversity of Bacteria and Archaea, the most ancient and most widespread forms of life on Earth, is a subject of intense controversy. This controversy stems largely from the fact that existing estimates are entirely based on theoretical models or extrapolations from small and biased data sets. Here, in an attempt to census the bulk of Earth's bacterial and archaeal ("prokaryotic") clades and to estimate their overall global richness, we analyzed over 1.7 billion 16S ribosomal RNA amplicon sequences in the V4 hypervariable region obtained from 492 studies worldwide, covering a multitude of environments and using multiple alternative primers. From this data set, we recovered 739,880 prokaryotic operational taxonomic units (OTUs, 16S-V4 gene clusters at 97% similarity), a commonly used measure of microbial richness. Using several statistical approaches, we estimate that there exist globally about 0.8-1.6 million prokaryotic OTUs, of which we recovered somewhere between 47%-96%, representing >99.98% of prokaryotic cells. Consistent with this conclusion, our data set independently "recaptured" 91%-93% of 16S sequences from multiple previous global surveys, including PCR-independent metagenomic surveys. The distribution of relative OTU abundances is consistent with a log-normal model commonly observed in larger organisms; the total number of OTUs predicted by this model is also consistent with our global richness estimates. By combining our estimates with the ratio of full-length versus partial-length (V4) sequence diversity in the SILVA sequence database, we further estimate that there exist about 2.2-4.3 million full-length OTUs worldwide. When restricting our analysis to the Americas, while controlling for the number of studies, we obtain similar richness estimates as for the global data set, suggesting that most OTUs are globally distributed. Qualitatively similar results are also obtained for other 16S similarity thresholds (90%, 95%, and 99%). Our estimates constrain the extent of a poorly quantified rare microbial biosphere and refute recent predictions that there exist trillions of prokaryotic OTUs.
| S-EPMC6361415 | biostudies-literature
Project description:Crisis motivates people to track news closely, and this increased engagement can expose individuals to politically sensitive information unrelated to the initial crisis. We use the case of the COVID-19 outbreak in China to examine how crisis affects information seeking in countries that normally exert significant control over access to media. The crisis spurred censorship circumvention and access to international news and political content on websites blocked in China. Once individuals circumvented censorship, they not only received more information about the crisis itself but also accessed unrelated information that the regime has long censored. Using comparisons to democratic and other authoritarian countries also affected by early outbreaks, the findings suggest that people blocked from accessing information most of the time might disproportionately and collectively access that long-hidden information during a crisis. Evaluations resulting from this access, negative or positive for a government, might draw on both current events and censored history.
| S-EPMC8794877 | biostudies-literature
Project description:As machine learning (ML) models gain traction in clinical applications, understanding the impact of clinician and societal biases on ML models is increasingly important. While biases can arise in the labels used for model training, the many sources from which these biases arise are not yet well-studied. In this paper, we highlight disparate censorship (i.e., differences in testing rates across patient groups) as a source of label bias that clinical ML models may amplify, potentially causing harm. Many patient risk-stratification models are trained using the results of clinician-ordered diagnostic and laboratory tests of labels. Patients without test results are often assigned a negative label, which assumes that untested patients do not experience the outcome. Since orders are affected by clinical and resource considerations, testing may not be uniform in patient populations, giving rise to disparate censorship. Disparate censorship in patients of equivalent risk leads to undertesting in certain groups, and in turn, more biased labels for such groups. Using such biased labels in standard ML pipelines could contribute to gaps in model performance across patient groups. Here, we theoretically and empirically characterize conditions in which disparate censorship or undertesting affect model performance across subgroups. Our findings call attention to disparate censorship as a source of label bias in clinical ML models.
| S-EPMC10162497 | biostudies-literature
Project description:Nitro aromatics have broad applications in industry, agriculture, and pharmaceutics. However, their industrial production is faced with many challenges including poor selectivity, heavy pollution and safety concerns. Nature provides multiple strategies for aromatic nitration, which opens the door for the development of green and efficient biocatalysts. Our group's efforts focused on a unique bacterial cytochrome P450 TxtE that originates from the biosynthetic pathway of phytotoxin thaxtomins, which can install a nitro group at C4 of l-Trp indole ring. TxtE is a Class I P450 and its reaction relies on a pair of redox partners ferredoxin and ferredoxin reductase for essential electron transfer. To develop TxtE as an efficient nitration biocatalyst, we created artificial self-sufficient P450 chimeras by fusing TxtE with the reductase domain of the bacterial P450BM3 (BM3R). We evaluated the catalytic performance of the chimeras with different lengths of the linker connecting TxtE and BM3R domains and identified one with a 14-amino-acid linker (TB14) to give the best activity. In addition, we demonstrated the broad substrate scope of the engineered biocatalyst by screening diverse l-Trp analogs. In this chapter, we provide a detailed procedure for the development of aromatic nitration biocatalysts, including the construction of P450 fusion chimeras, biochemical characterization, determination of catalytic parameters, and testing of enzyme-substrate scope. These protocols can be followed to engineer other P450 enzymes and illustrate the processes of biocatalytic development for the synthesis of nitro chemicals.
| S-EPMC10928822 | biostudies-literature
Project description:Knowledge of bacterial lipolytic enzymes is increasing at a rapid and exciting rate. To obtain an overview of this industrially very important class of enzymes and their characteristics, we have collected and classified the information available from protein and nucleotide databases. Here we propose an updated and extensive classification of bacterial esterases and lipases based mainly on a comparison of their amino acid sequences and some fundamental biological properties. These new insights result in the identification of eight different families with the largest being further divided into six subfamilies. Moreover, the classification enables us to predict (1) important structural features such as residues forming the catalytic site or the presence of disulphide bonds, (2) types of secretion mechanism and requirement for lipase-specific foldases, and (3) the potential relationship to other enzyme families. This work will therefore contribute to a faster identification and to an easier characterization of novel bacterial lipolytic enzymes.
| S-EPMC1220539 | biostudies-other
Project description:Small proteins are an emerging class of gene products with diverse roles in bacterial physiology. However, a full understanding of their importance has been hampered by insufficient genome annotations and a lack of characterization in microbes other than Escherichia coli. Here, we have taken an integrative approach to accelerate the discovery of small proteins and their putative virulence-associated functions in Salmonella Typhimurium. We merged the annotated small proteome of Salmonella with new small proteins predicted with in silico and experimental approaches. We then exploited existing and newly generated global datasets that provide information on small open reading frame expression during infection of epithelial cells (dual RNA-seq), contribution to bacterial fitness inside macrophages (TraDIS), and potential engagement in molecular interactions (Grad-seq). This integrative approach suggested a new role for the small protein MgrB beyond its known function in regulating PhoQ. We demonstrated a virulence and motility defect of a Salmonella ΔmgrB mutant and revealed an effect of MgrB in regulating the Salmonella transcriptome and proteome under infection-relevant conditions. Overall, our study highlights the power of interpreting available “omics” datasets with a focus on small proteins, and may serve as a blueprint for a data integration-based survey of small proteins in diverse bacteria.
2020-11-22 | GSE149928 | GEO
Project description:Our study highlights the power of interpreting available “omics” datasets with a focus on small proteins, and may serve as a blueprint for a data integration-based survey of small proteins in diverse bacteria.
2020-11-17 | GSE149893 | GEO
Project description:Small proteins are an emerging class of gene products with diverse roles in bacterial physiology. However, a full understanding of their importance has been hampered by insufficient genome annotations and a lack of characterization in microbes other than Escherichia coli. Here, we have taken an integrative approach to accelerate the discovery of small proteins and their putative virulence-associated functions in Salmonella Typhimurium. We merged the annotated small proteome of Salmonella with new small proteins predicted with in silico and experimental approaches. We then exploited existing and newly generated global datasets that provide information on small open reading frame expression during infection of epithelial cells (dual RNA-seq), contribution to bacterial fitness inside macrophages (TraDIS), and potential engagement in molecular interactions (Grad-seq). This integrative approach suggested a new role for the small protein MgrB beyond its known function in regulating PhoQ. We demonstrated a virulence and motility defect of a Salmonella ΔmgrB mutant and revealed an effect of MgrB in regulating the Salmonella transcriptome and proteome under infection-relevant conditions. Overall, our study highlights the power of interpreting available “omics” datasets with a focus on small proteins, and may serve as a blueprint for a data integration-based survey of small proteins in diverse bacteria.
2020-11-20 | GSE149580 | GEO
Project description:Attachment of ubiquitin molecules to protein substrates is a reversible post-translational modification (PTM), which occurs ubiquitously in eukaryotic cells and controls most cellular processes. As a consequence, ubiquitination is an attractive target of pathogen-encoded virulence factors. Pathogenic bacteria have evolved multiple mechanisms to hijack the host's ubiquitin system to their advantage. In this review, we discuss the bacteria-encoded E3 ligases and deubiquitinases translocated to the host for an addition or removal of eukaryotic ubiquitin modification, effectively hijacking the host's ubiquitination processes. We review bacterial enzymes homologous to host proteins in sequence and functions, as well as enzymes with novel mechanisms in ubiquitination, which have significant structural differences in comparison to the mammalian E3 ligases. Finally, we will also discuss examples of molecular "counter-weapons" - eukaryotic proteins, which counteract pathogen-encoded E3 ligases. The many examples of the pathogen effector molecules that catalyze eukaryotic ubiquitin modification bring to light the intricate pathways involved in the pathogenesis of some of the most virulent bacterial infections with human pathogens. The role of these effector molecules remains an essential determinant of bacterial virulence in terms of infection, invasion, and replication. A comprehensive understanding of the mechanisms dictating the mimicry employed by bacterial pathogens is of vital importance in developing new strategies for therapeutic approaches.
| S-EPMC7369425 | biostudies-literature