The Azurin Coding Gene: Origin and Phylogenetic Distribution

Azurin is a bacterial-derived cupredoxin, which is mainly involved in electron transport reactions. Interest in azurin protein has risen in recent years due to its anticancer activity and its possible applications in anticancer therapies. Nevertheless, the attention of the scientific community only focused on the azurin protein found in Pseudomonas aeruginosa (Proteobacteria, Gammaproteobacteria). In this work, we performed the first comprehensive screening of all the bacterial genomes available in online repositories to assess azurin distribution in the three domains of life. The Azurin coding gene was not detected in the domains Archaea and Eucarya, whereas it was detected in phyla other than Proteobacteria, such as Bacteroidetes, Verrucomicrobia and Chloroflexi, and a phylogenetic analysis of the retrieved sequences was performed. Observed patchy distribution and phylogenetic data suggest that once it appeared in the bacterial domain, the azurin coding gene was lost in several bacterial phyla and/or anciently horizontally transferred between different phyla, even though a vertical inheritance appeared to be the major force driving the transmission of this gene. Interestingly, a shared conserved domain has been found among azurin members of all the investigated phyla. This domain is already known in P. aeruginosa as p28 domain and its importance for azurin anticancer activity has been widely explored. These findings may open a new and intriguing perspective in deciphering the azurin anticancer mechanisms and to develop new tools for treating cancer diseases.

Cell wall synthesis and remodeling dynamics determine bacterial division site architecture and cell shape

The bacterial division apparatus builds daughter cell poles by catalyzing the synthesis and remodeling of the septal peptidoglycan (sPG) cell wall. Understanding of this essential process has been limited by the lack of native three-dimensional visualization of developing septa. Here, we used state-of-the-art cryogenic electron tomography (cryo-ET) and fluorescence microscopy to understand the division site architecture and sPG biogenesis dynamics of the Gram-negative bacterium Escherichia coli. Our results with mutant cells altered in the regulation of sPG biogenesis revealed a striking and unexpected similarity between the architecture of E. coli septa with those from Gram-positive bacteria, suggesting a conserved morphogenic mechanism. Furthermore, we found that the cell elongation and division machineries are in competition and that their relative activities determine the shape of cell constrictions and the poles they form. Overall, our results highlight how the activity of the division system can be modulated to generate the diverse array of morphologies observed in the bacterial domain.

A non-radioactive mass spectrometry based differential radial capillary action of ligand assay (DRaCALA) to assess ligand binding to proteins

Binding of ligands to macromolecules changes their physicochemical characteristics. Cyclic di-GMP and other cyclic di-nucleotides are second messengers involved in motility/sessility and acute/chronic infection life style transition. Although the GGDEF domain encoding preferentially a diguanylate cyclase represents one of the most abundant bacterial domain superfamilies, the number of cyclic di-GMP receptors falls short. To facilitate screening for cyclic di-nucleotide binding proteins, we describe a non-radioactive, MALDI-TOF based modification of the widely applied differential radial capillary action of ligand assay (DRaCALA). The results of this assay suggest that YciRFec101, but not the YciRTOB1 variant of the diguanylate cyclase/phosphodiesterase YciR binds cyclic di-GMP.

Identical sequences found in distant genomes reveal frequent horizontal transfer across the bacterial domain

Horizontal Gene Transfer (HGT) is an essential force in microbial evolution. Despite detailed studies on a variety of systems, a global picture of HGT in the microbial world is still missing. Here, we exploit that HGT creates long identical DNA sequences in the genomes of distant species, which can be found efficiently using alignment-free methods. Our pairwise analysis of 93 481 bacterial genomes identified 138 273 HGT events. We developed a model to explain their statistical properties as well as estimate the transfer rate between pairs of taxa. This reveals that long-distance HGT is frequent: our results indicate that HGT between species from different phyla has occurred in at least 8% of the species. Finally, our results confirm that the function of sequences strongly impacts their transfer rate, which varies by more than 3 orders of magnitude between different functional categories. Overall, we provide a comprehensive view of HGT, illuminating a fundamental process driving bacterial evolution.

Dichloromethane Degradation Pathway from Unsequenced Hyphomicrobium sp. MC8b Rapidly Explored by Pan-Proteomics

Several bacteria are able to degrade the major industrial solvent dichloromethane (DCM) by using the conserved dehalogenase DcmA, the only system for DCM degradation characterised at the sequence level so far. Using differential proteomics, we rapidly identified key determinants of DCM degradation for Hyphomicrobium sp. MC8b, an unsequenced facultative methylotrophic DCM-degrading strain. For this, we designed a pan-proteomics database comprising the annotated genome sequences of 13 distinct Hyphomicrobium strains. Compared to growth with methanol, growth with DCM induces drastic changes in the proteome of strain MC8b. Dichloromethane dehalogenase DcmA was detected by differential pan-proteomics, but only with poor sequence coverage, suggesting atypical characteristics of the DCM dehalogenation system in this strain. More peptides were assigned to DcmA by error-tolerant search, warranting subsequent sequencing of the genome of strain MC8b, which revealed a highly divergent set of dcm genes in this strain. This suggests that the dcm enzymatic system is less strongly conserved than previously believed, and that substantial molecular evolution of dcm genes has occurred beyond their horizontal transfer in the bacterial domain. Our study showed the power of pan-proteomics for quick characterization of new strains belonging to branches of the Tree of Life that are densely genome-sequenced.

A Comparison of Two DNA Metagenomic Bioinformatic Pipelines While Evaluating the Microbial Diversity in Feces of Tanzanian Small Holder Dairy Cattle

Analysis of shotgun metagenomic data generated from next generation sequencing platforms can be done through a variety of bioinformatic pipelines. These pipelines employ different sets of sophisticated bioinformatics algorithms which may affect the results of this analysis. In this study, we compared two commonly used pipelines for shotgun metagenomic analysis: MG-RAST and Kraken 2, in terms of taxonomic classification, diversity analysis, and usability using their primarily default parameters. Overall, the two pipelines detected similar abundance distributions in the three most abundant taxa Proteobacteria, Firmicutes, and Bacteroidetes. Within bacterial domain, 497 genera were identified by both pipelines, while an additional 694 and 98 genera were solely identified by Kraken 2 and MG-RAST, respectively. 933 species were detected by the two algorithms. Kraken 2 solely detected 3550 species, while MG-RAST identified 557 species uniquely. For archaea, Kraken 2 generated 105 and 236 genera and species, respectively, while MG-RAST detected 60 genera and 88 species. 54 genera and 72 species were commonly detected by the two methods. Kraken 2 had a quicker analysis time (~4 hours) while MG-RAST took approximately 2 days per sample. This study revealed that Kraken 2 and MG-RAST generate comparable results and that a reliable high-level overview of sample is generated irrespective of the pipeline selected. However, Kraken 2 generated a more accurate taxonomic identification given the higher number of “Unclassified” reads in MG-RAST. The observed variations at the genus level show that a main restriction is using different databases for classification of the metagenomic data. The results of this research indicate that a more inclusive and representative classification of microbiomes may be achieved through creation of the combined pipelines.

A Comparison of Two DNA Metagenomic Bioinformatic Pipelines while evaluating the Microbial Diversity in feces of Tanzanian small holder dairy cattle

Background: Analysis of shotgun metagenomic data generated from next generation sequencing platforms can be done through a variety of bioinformatic pipelines. These pipelines employ different sets of sophisticated bioinformatics algorithms which may affect the results of this analysis. Furthermore, no conventional assessment technique for estimating the precision of each pipeline exists and few studies have been carried out to compare the characteristics, benefits and disadvantages of each pipeline. In this study we compared two commonly used pipelines for shotgun metagenomic analysis: MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Kraken, in terms of taxonomic classification, diversity analysis and usability using their primarily default parametersResults: Overall, the two pipelines detected similar abundance distributions in the three most abundant taxa Proteobacteria, Firmicutes and Bacteroidetes. Within bacterial domain, 497 genera were identified by both pipelines, while an additional 694 and 98 genera were solely identified by Kraken and MG-RAST respectively. 933 species were detected by the two algorithms. Kraken solely detected 3550 species, while MG-RAST identified 557 species uniquely. For archaea, Kraken generated 105 and 236 genera and species respectively while MG-RAST detected 60 genera and 88 species. 54 genera and 72 species were commonly detected by the two methods. Kraken had a quicker analysis time (~4 hours) while MG-RAST took approximately 2 days per sample.Conclusions: This study revealed that Kraken and MG-RAST generate comparable results and that a reliable high-level overview of sample is generated irrespective of the pipeline selected. The observed variations at the genus level show that a main restriction is using different databases for classification of the metagenomic data. Specifically, the pipelines could have been limited because some rumen microbes lack reference genomes. The results of this research indicate that a more inclusive and representative classification of microbiomes may be achieved through creation of combined pipelines.

Transcriptional Responses to ppGpp and DksA

The stringent response to nutrient deprivation is a stress response found throughout the bacterial domain of life. Although first described in proteobacteria for matching ribosome synthesis to the cell's translation status and for preventing formation of defective ribosomal particles, the response is actually much broader, regulating many hundreds of genes—some positively, some negatively. Utilization of the signaling molecules ppGpp and pppGpp for this purpose is ubiquitous in bacterial evolution, although the mechanisms employed vary. In proteobacteria, the signaling molecules typically bind to two sites on RNA polymerase, one at the interface of the β′ and ω subunits and one at the interface of the β′ secondary channel and the transcription factor DksA. The β′ secondary channel is targeted by other transcription regulators as well. Although studies on the transcriptional outputs of the stringent response date back at least 50 years, the mechanisms responsible are only now coming into focus.