Investigation of the presence of an aliphatic biopolymer in cyanobacteria: Implications for kerogen formation

Algaenan has been suggested to be one of the main precursors of certain kerogens. It is a non-hydrolysable and insoluble biomolecule of high molecular weight. It has been found in a limited number of microalgae species. There is considerable uncertainty about its formation and preservation, as well as its role in kerogen formation and the implications for the global C cycle. We tested whether the cyanobacterium Chlorogloeopsis fritschii can synthesise a biomacromolecule similar to algaenan with potential to contribute to kerogen via selective preservation. Two freshwater green microalgae, Pseudochoricystis ellipsoidea and Scenedesmus obliquus, as well as C. fritschii, were subjected to harsh solvent extraction and hydrolysis steps to obtain an insoluble and non-hydrolysable macromolecule. The residues from all three species were analysed using pyrolysis–gas chromatography–mass spectrometry and solid-state nuclear magnetic resonance spectroscopy. The analysis revealed that C. fritschii indeed contains a resistant biomacromolecule exhibiting the characteristic aliphatic structure of algaenan, similar to the algaenan residues from the two microalgae. Due to the robust nature of Chlorogloeopsis compared with eukaryotes, it can prevail in extreme environmental conditions such as freezing, thawing, desiccation and overheating – conditions prevalent on the primeval earth. The presence of a resistant aliphatic biopolymer in Chlorogloeopsis suggests that cyanobacteria could have contributed to kerogen via selective preservation

Structure and Inhibition of Microbiome β-Glucuronidases Essential to the Alleviation of Cancer Drug Toxicity

SummaryThe selective inhibition of bacterial β-glucuronidases was recently shown to alleviate drug-induced gastrointestinal toxicity in mice, including the damage caused by the widely used anticancer drug irinotecan. Here, we report crystal structures of representative β-glucuronidases from the Firmicutes Streptococcus agalactiae and Clostridium perfringens and the Proteobacterium Escherichia coli, and the characterization of a β-glucuronidase from the Bacteroidetes Bacteroides fragilis. While largely similar in structure, these enzymes exhibit marked differences in catalytic properties and propensities for inhibition, indicating that the microbiome maintains functional diversity in orthologous enzymes. Small changes in the structure of designed inhibitors can induce significant conformational changes in the β-glucuronidase active site. Finally, we establish that β-glucuronidase inhibition does not alter the serum pharmacokinetics of irinotecan or its metabolites in mice. Together, the data presented advance our in vitro and in vivo understanding of the microbial β-glucuronidases, a promising new set of targets for controlling drug-induced gastrointestinal toxicity

The khmer software package: enabling efficient nucleotide sequence analysis

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/

The khmer software package: enabling efficient nucleotide sequence analysis [version 1; referees: 2 approved, 1 approved with reservations]

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/

NCBI’s virus discovery codeathon: building “FIVE” —the Federated Index of Viral Experiments API index

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE