Mycoplasma synoviae infection rates in chickens are increasing worldwide. Genomic studies have considerably improved our understanding of M. synoviae biology and virulence. However, approximately 20% of the predicted proteins have unknown functions. In particular, the M. synoviae ATCC 25204 genome has 663 encoding DNA sequences, among which 155 are considered encoding hypothetical proteins (HPs). Several of these genes may encode unknown virulence factors. This study aims to reannotate all 155 proteins in M. synoviae ATCC 25204 to predict new potential virulence factors using currently available databases and bioinformatics tools. Finally, 125 proteins were reannotated, including enzymes (39%), lipoproteins (10%), DNA-binding proteins (6%), phase-variable hemagglutinin (19%), and other protein types (26%). Among 155 proteins, 28 proteins associated with virulence were detected, five of which were reannotated. Furthermore, HP expression was compared before and after the M. synoviae infection of cells to identify potential virulence-related proteins. The expression of 14 HP genes was upregulated, including that of five virulence-related genes. Our study improved the functional annotation of M. synoviae ATCC 25204 from 76% to 95% and enabled the discovery of potential virulence factors in the genome. Moreover, 14 proteins that may be involved in M. synoviae infection were identified, providing candidate proteins and facilitating the exploration of the infection mechanism of M. synoviae.

Hypothetical proteins (HPs) are non-predicted sequences that are identified only by open reading frames in sequenced genomes, but their protein products remain uncharacterized by any experimental means. The genome of every species consists of HPs that are involved in various cellular processes and signaling pathways. Annotation of HPs is important as they play a key role in disease mechanisms, drug designing, vaccine production, antibiotic production, and host adaptation. In the case of bacteria, 25-50% of the genome comprises HPs, which are involved in metabolic pathways and pathogenesis. The characterization of bacterial HPs helps to identify virulent proteins that are involved in pathogenesis. This can be done using in-silico studies, which provide sequence analogs, physiochemical properties, cellular or subcellular localization, structure and function validation, and protein-protein interactions. The most diverse types of virulent proteins are exotoxins, endotoxins, and adherent virulent factors that are encoded by virulent genes present on the chromosomal DNA of the bacteria. This review evaluates virulent HPs of pathogenic bacteria, such as Staphylococcus aureus, Chlamydia trachomatis, Fusobacterium nucleatum, and Yersinia pestis. The potential of these HPs as a drug target in bacteria-caused infectious diseases, along with the mode of action and treatment approaches, has been discussed.

Cadmium is a non-essential toxic heavy metal for organisms, including plants and cyanobacteria. Cadmium resistance transporters involved in resistance of cells against various toxicants such as drugs and effluxes cytotoxic compounds from cells. However, cadmium resistance-associated protein (CadD) has never been reported from a diazotrophic cyanobacterium Anabaena sp. To test whether the hypothetical protein All3255 of Anabaena sp. PCC7120 a homolog of cadmium resistance-associated protein (CadD) involved in cadmium or heavy metal resistance or not, cloning and heterologous expression analysis of all3255 performed in Escherichia coli BL21 (DE3). Our results revealed that the strain transformed with pGEX-5X-2 + all3255 showed resistant towards not only to cadmium but also other heavy metals such as nickel, copper, zinc, lead and cobalt in addition to arsenic than those of transformed with empty vector (pGEX-5X-2). Furthermore, the results of metal accumulation analysis of these cells unveil a lower accumulation of tested heavy metals in all3255-overexpressing E. coli cells than those transformed with empty vector. This study strongly supports the role of All3255 of Anabaena sp. PCC7120 as a CadD efflux pump of heavy metals in E.coli.

Helicobacter pylori is a Gram-negative bacteria that is responsible for gastritis in human. Its spiral flagellated body helps in locomotion and colonization in the host environment. It is capable of living in the highly acidic environment of the stomach with the help of acid adaptive genes. The genome of H. pylori 26695 strain contains 1,555 coding genes that encode 1,445 proteins. Out of these, 340 proteins are characterized as hypothetical proteins (HP). This study involves extensive analysis of the HPs using an established pipeline which comprises various bioinformatics tools and databases to find out probable functions of the HPs and identification of virulence factors. After extensive analysis of all the 340 HPs, we found that 104 HPs are showing characteristic similarities with the proteins with known functions. Thus, on the basis of such similarities, we assigned probable functions to 104 HPs with high confidence and precision. All the predicted HPs contain representative members of diverse functional classes of proteins such as enzymes, transporters, binding proteins, regulatory proteins, proteins involved in cellular processes and other proteins with miscellaneous functions. Therefore, we classified 104 HPs into aforementioned functional groups. During the virulence factors analysis of the HPs, we found 11 HPs are showing significant virulence. The identification of virulence proteins with the help their predicted functions may pave the way for drug target estimation and development of effective drug to counter the activity of that protein.

Functional inference of hypothetical proteins (HPs) is a significant task in the post-genomic era. We described here a network-based protocol for functional inference of HPs using experimental transcriptomic, proteomic, and protein-protein interaction (PPI) datasets. The protocol includes two steps: i) co-expression networks were constructed using large proteomic or transcriptomic datasets of Synechocystis sp. PCC 6803 under various stress conditions, and then combined with a Synechocystis PPI network to generate bi-colored networks that include both annotated proteins and HPs; ii) a global algorithm was adapted to the bi-colored networks for functional inference of HPs. The algorithm ranked the associations between genes/proteins with known GO functional categories, and assumed that the top one ranked HP for each GO functional category might have a function related to the GO functional category. We applied the protocol to all HPs of the model cyanobacterium Synechocystis, and were able to assign putative functions to 122 HPs that have never been functionally characterized previously. Finally, the functional inference was validated by the known biological information of operon, and results showed that more than 70% HPs could be correctly validated. The study provided a new protocol to integrate different types of OMICS datasets for functional inference of HPs, and could be useful in achieving new insights into the Synechocystis metabolism.