The phytopathogenic bacteria, Pseudomonas syringae pv. lapsa (P. syringae pv. lapsa) infects the staple food crop wheat. Metalloproteins play important roles in plant-pathogen interactions. Hence, the present work is aimed to predict and analyze the iron (Fe), zinc (Zn), and copper (Cu) binding proteins of P. syringae pv. lapsa which help in its growth, adaptation, survival and pathogenicity. A total of 232 Fe, 307 Zn, and 38 Cu-binding proteins have been identified. The functional annotation, subcellular localization and gene ontology enriched network analysis revealed their role in wide range of biological activities of the phytopathogen. Among the identified metalloproteins, a total of 29 Fe-binding, 31 Zn-binding, and 5 Cu-binding proteins were found to be secreted in nature. These putative secreted metalloproteins may perform diverse cellular and biological functions ranging from transport, response to oxidative stress, proteolysis, antimicrobial resistance, metabolic processes, protein folding and DNA repair. The observations obtained here may provide initial information required to draft new schemes to control microbial infections of staple food crops and will further help in developing sustainable agriculture.

Approximately one-third of all proteins have been estimated to contain at least one metal cofactor, and these proteins are referred to as metalloproteins. These represent one of the most diverse classes of proteins, containing metal ions that bind to specific sites to perform catalytic, regulatory and structural functions. Bioinformatic tools have been developed to predict metalloproteins encoded by an organism based only on its genome sequence. Its function and the type of metal binder can also be predicted via a bioinformatics approach. Paracoccidioides complex includes termodimorphic pathogenic fungi that are found as saprobic mycelia in the environment and as yeast, the parasitic form, in host tissues. They are the etiologic agents of Paracoccidioidomycosis, a prevalent systemic mycosis in Latin America. Many metalloproteins are important for the virulence of several pathogenic microorganisms. Accordingly, the present work aimed to predict the copper, iron and zinc proteins encoded by the genomes of three phylogenetic species of Paracoccidioides (Pb01, Pb03, and Pb18). The metalloproteins were identified using bioinformatics approaches based on structure, annotation and domains. Cu-, Fe-, and Zn-binding proteins represent 7% of the total proteins encoded by Paracoccidioides spp. genomes. Zinc proteins were the most abundant metalloproteins, representing 5.7% of the fungus proteome, whereas copper and iron proteins represent 0.3 and 1.2%, respectively. Functional classification revealed that metalloproteins are related to many cellular processes. Furthermore, it was observed that many of these metalloproteins serve as virulence factors in the biology of the fungus. Thus, it is concluded that the Cu, Fe, and Zn metalloproteomes of the Paracoccidioides spp. are of the utmost importance for the biology and virulence of these particular human pathogens.

The ubiquitous involvement of key iron-containing metalloenzymes in metabolism is reflected in the dependence of virtually all bacteria on iron for growth and, thereby, potentially provides multiple biomolecular targets for antimicrobial killing. We hypothesized that nitrosative stress, which induces damage to iron metalloproteins, would sensitize bacteria to the ferric iron mimic gallium(III) (Ga3+), potentially providing a novel therapeutic combination. Using both laboratory and clinical isolates of Pseudomonas aeruginosa, we herein demonstrate that Ga3+ and sodium nitrite synergistically inhibit bacterial growth under both aerobic and anaerobic conditions. Nitric oxide also potentiated the antimicrobial effect of Ga3+. Because many chronic pulmonary infections are found as biofilms and biofilms have very high antibiotic tolerance, we then tested the combination against biofilms grown on plastic surfaces, as well as the apical surface of airway epithelial cells. Ga3+ and sodium nitrite had synergistic antimicrobial activity against both biofilms grown on plastic and on airway epithelial cell. Both Ga3+ and various NO donors are (independently) in clinical development as potential antimicrobials, however, we now propose the combination to have some particular advantages, while anticipating it should ultimately prove similarly safe for translation to treatment of human disease.

Cyanide is a toxic compound widely used in mining and jewelry industries, as well as in the synthesis of many different chemicals. Cyanide toxicity derives from its high affinity for metals, which causes inhibition of relevant metalloenzymes. However, some cyanide-degrading microorganisms like the alkaliphilic bacterium Pseudomonas pseudoalcaligenes CECT5344 may detoxify hazardous industrial wastewaters that contain elevated cyanide and metal concentrations. Considering that iron availability is strongly reduced in the presence of cyanide, mechanisms for iron homeostasis should be required for cyanide biodegradation. Previous omic studies revealed that in the presence of a cyanide-containing jewelry residue the strain CECT5344 overproduced the dihydrodipicolinate synthase DapA1, a protein involved in lysine metabolism that also participates in the synthesis of dipicolinates, which are excellent metal chelators. In this work, a dapA1 - mutant of P. pseudoalcaligenes CECT5344 has been generated and characterized. This mutant showed reduced growth and cyanide consumption in media with the cyanide-containing wastewater. Intracellular levels of metals like iron, copper and zinc were increased in the dapA1 - mutant, especially in cells grown with the jewelry residue. In addition, a differential quantitative proteomic analysis by LC-MS/MS was carried out between the wild-type and the dapA1 - mutant strains in media with jewelry residue. The mutation in the dapA1 gene altered the expression of several proteins related to urea cycle and metabolism of arginine and other amino acids. Additionally, the dapA1 - mutant showed increased levels of the global nitrogen regulator PII and the glutamine synthetase. This proteomic study has also highlighted that the DapA1 protein is relevant for cyanide resistance, oxidative stress and iron homeostasis response, which is mediated by the ferric uptake regulator Fur. DapA1 is required to produce dipicolinates that could act as iron chelators, conferring protection against oxidative stress and allowing the regeneration of Fe-S centers to reactivate cyanide-damaged metalloproteins.

Reliable functional annotation of genomic data is the key-step in the discovery of novel enzymes. Intrinsic sequencing data quality problems of single amplified genomes (SAGs) and poor homology of novel extremophile's genomes pose significant challenges for the attribution of functions to the coding sequences identified. The anoxic deep-sea brine pools of the Red Sea are a promising source of novel enzymes with unique evolutionary adaptation. Sequencing data from Red Sea brine pool cultures and SAGs are annotated and stored in the Integrated Data Warehouse of Microbial Genomes (INDIGO) data warehouse. Low sequence homology of annotated genes (no similarity for 35% of these genes) may translate into false positives when searching for specific functions. The Profile and Pattern Matching (PPM) strategy described here was developed to eliminate false positive annotations of enzyme function before progressing to labor-intensive hyper-saline gene expression and characterization. It utilizes InterPro-derived Gene Ontology (GO)-terms (which represent enzyme function profiles) and annotated relevant PROSITE IDs (which are linked to an amino acid consensus pattern). The PPM algorithm was tested on 15 protein families, which were selected based on scientific and commercial potential. An initial list of 2577 enzyme commission (E.C.) numbers was translated into 171 GO-terms and 49 consensus patterns. A subset of INDIGO-sequences consisting of 58 SAGs from six different taxons of bacteria and archaea were selected from six different brine pool environments. Those SAGs code for 74,516 genes, which were independently scanned for the GO-terms (profile filter) and PROSITE IDs (pattern filter). Following stringent reliability filtering, the non-redundant hits (106 profile hits and 147 pattern hits) are classified as reliable, if at least two relevant descriptors (GO-terms and/or consensus patterns) are present. Scripts for annotation, as well as for the PPM algorithm, are available through the INDIGO website.