Draft genomes of three Antarctic Psychrobacter strains producing antimicrobial compounds against Burkholderia cepacia complex, opportunistic human pathogens

Draft genome sequence of Psychrobacter nivimaris LAMA 639 and its biotechnological potential

Bacteria of the genus Psychrobacter are known for their psychrophilic characteristics, being extremophilic organisms capable of surviving and reproducing in hostile environments of low temperature and high pressure. Among many of the genus characteristics, there is the ability to produce enzymes and molecules of industrial biotechnology importance, such as pigments and proteins related to heavy metal bioremediation. The bacterium strain Psychrobacter nivimaris LAMA 639 was isolated from sediments from the Walvis Ridge ocean crest at a depth of 4.400 m (33.40 S 2.35 E). It is a nonmotile, halotolerant, cream-colored gram-negative aerobic bacterium. Its cultivation was performed in marine agar plates and inoculated into test tubes with NaCl at an optimal temperature of 30 °C and with shaking at 100 rpm. Genome extraction was performed with the DNeasy Blood & Tissue Kit (QIAGEN®). Sequencing was performed by Macrogen using the NovaSeq® 6000 platform (Illumina) applying the whole genome shotgun (WGS) method. Thereafter, 14.712.526 reads of 151 bp were generated, totaling 2.2 G bp with a GC content of 42.9%. Assembly and mapping were performed with a CLC Genomics Workbench. The best assembly considered was the one with the lowest number of contigs and the highest base length pair. The assemblies were evaluated using QUAST, and the best resulting variant was selected for annotation. Genome annotation was performed with RAST and PATRIC; the antiSMASH tool was used for secondary metabolites; NaPDoS was used for domains; and three-dimensional structural prediction of relevant proteins was performed using Phyre2. Annotation with ClassicRAST generated 2,891 coding sequences (CDSs) distributed in 402 subsystems. Annotation with PATRIC generated 2,896 coding sequences, among them 776 hypothetical proteins. The antiSMASH tool visualized a beta-lactone cluster in contig 06. In the search for natural products with NaPDoS, two ketosynthase domains were identified. The search for relevant proteins was performed using the AMFEP list as a criterion. From these data, 34 possible enzymes with biotechnological potential were found. Finally, the organism is presented as a new reference regarding the potential of deep-sea marine bacteria, demonstrating that, from the annotated and cured genome, it is possible to find in its genetic repertory products of interest for biotechnological applications.

The transcriptome of Listeria monocytogenes during co-cultivation with cheese rind bacteria suggests adaptation by induction of ethanolamine and 1,2-propanediol catabolism pathway genes

The survival of Listeria (L.) monocytogenes in foods and food production environments (FPE) is dependent on several genes that increase tolerance to stressors; this includes competing with intrinsic bacteria. We aimed to uncover genes that are differentially expressed (DE) in L. monocytogenes sequence type (ST) 121 strain 6179 when co-cultured with cheese rind bacteria. L. monocytogenes was cultivated in broth or on plates with either a Psychrobacter or Brevibacterium isolate from cheese rinds. RNA was extracted from co-cultures in broth after two or 12 hours and from plates after 24 and 72 hours. Broth co-cultivations with Brevibacterium or Psychrobacter yielded up to 392 and 601 DE genes, while plate co-cultivations significantly affected the expression of up to 190 and 485 L. monocytogenes genes, respectively. Notably, the transcription of virulence genes encoding the Listeria adhesion protein and Listeriolysin O were induced during plate and broth co-cultivations. The expression of several systems under the control of the global stress gene regulator, σB, increased during co-cultivation. A cobalamin-dependent gene cluster, responsible for the catabolism of ethanolamine and 1,2-propanediol, was upregulated in both broth and plate co-cultures conditions. Finally, a small non-coding (nc)RNA, Rli47, was induced after 72 hours of co-cultivation on plates and accounted for 50-90% of the total reads mapped to L. monocytogenes. A recent study has shown that Rli47 may contribute to L. monocytogenes stress survival by slowing growth during stress conditions through the suppression of branch-chained amino acid biosynthesis. We hypothesize that Rli47 may have an impactful role in the response of L. monocytogenes to co-cultivation by regulating a complex network of metabolic and virulence mechanisms.

Porifera collection of the Italian National Antarctic Museum (MNA), with an updated checklist from Terra Nova Bay (Ross Sea)

This new dataset presents occurrence data for Porifera collected in the Ross Sea, mainly in the Terra Nova Bay area, and curated at the Italian National Antarctic Museum (MNA, section of Genoa). Specimens were collected in 331 different sampling stations at depths ranging from 17 to 1,100 meters in the framework of 17 different Italian Antarctic expeditions funded by the Italian National Antarctic Research Program (PNRA). A total of 807 specimens, belonging to 144 morphospecies (i.e., 95 taxa identified at species level and 49 classified at least at the genus level) is included in the dataset. Nearly half (45%) of the species reported here correspond to species already known for Terra Nova Bay. Out of the remaining 55% previously unknown records, under a third (~29%) were classified at the species level, while over a quarter (~26%) were ascribed to the genus level only and these would require further study. All vouchers are permanently curated at the MNA and are available for study to the scientific community. A 3D model of an uncommon species from the Ross Sea, i.e. Tethyopsisbrondstedi (Burton, 1929), is also presented and will be made available for outreach purposes.

Genomic and phenotypic characterization of the species Acinetobacter venetianus

Crude oil is a complex mixture of hydrocarbons and other organic compounds that can produce serious environmental problems and whose removal is highly demanding in terms of human and technological resources. The potential use of microbes as bioremediation agents is one of the most promising fields in this area. Members of the species Acinetobacter venetianus have been previously characterized for their capability to degrade n-alkanes and thus may represent interesting model systems to implement this process. Although a preliminary experimental characterization of the overall hydrocarbon degradation capability has been performed for five of them, to date, the genetic/genomic features underlying such molecular processes have not been identified. Here we have integrated genomic and phenotypic information for six A. venetianus strains, i.e. VE-C3, RAG-1^T, LUH 13518, LUH 7437, LUH 5627 and LUH 8758. Besides providing a thorough description of the A. venetianus species, these data were exploited to infer the genetic features (presence/absence patterns of genes) and the short-term evolutionary events possibly responsible for the variability in n-alkane degradation efficiency of these strains, including the mechanisms of interaction with the fuel droplet and the subsequent catabolism of this pollutant.

MeDuSa: a multi-draft based scaffolder

MOTIVATION

Completing the genome sequence of an organism is an important task in comparative, functional and structural genomics. However, this remains a challenging issue from both a computational and an experimental viewpoint. Genome scaffolding (i.e. the process of ordering and orientating contigs) of de novo assemblies usually represents the first step in most genome finishing pipelines.

RESULTS

In this article we present MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalizes the scaffolding problem by means of a combinatorial optimization formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries. This makes usability and running time two additional important features of our method. Moreover, benchmarks and tests on real bacterial datasets showed that MeDuSa is highly accurate and, in most cases, outperforms traditional scaffolders. The possibility to use MeDuSa on eukaryotic datasets has also been evaluated, leading to interesting results.