RESUMO
Secretion systems play a crucial role in microbe-microbe or host-microbe interactions. Among these systems, the extracellular contractile injection system (eCIS) is a unique bacterial and archaeal extracellular secretion system that injects protein toxins into target organisms. However, the specific proteins that eCISs inject into target cells and their functions remain largely unknown. Here, we developed a machine learning classifier to identify eCIS-associated toxins (EATs). The classifier combines genetic and biochemical features to identify EATs. We also developed a score for the eCIS N-terminal signal peptide to predict EAT loading. Using the classifier we classified 2,194 genes from 950 genomes as putative EATs. We validated four new EATs, EAT14-17, showing toxicity in bacterial and eukaryotic cells, and identified residues of their respective active sites that are critical for toxicity. Finally, we show that EAT14 inhibits mitogenic signaling in human cells. Our study provides insights into the diversity and functions of EATs and demonstrates machine learning capability of identifying novel toxins. The toxins can be employed in various applications dependently or independently of eCIS.
Assuntos
Aprendizado de Máquina , Humanos , Toxinas Bacterianas/genética , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismoRESUMO
The cytotoxic necrotizing factor (CNF) family of AB-type bacterial protein toxins catalyze two types of modification on their Rho GTPase substrates: deamidation and transglutamination. It has been established that E. coli CNF1 and its close homolog proteins catalyze primarily deamidation and Bordetella dermonecrotic toxin (DNT) catalyzes primarily transglutamination. The rapidly expanding microbial genome sequencing data have revealed that there are at least 13 full-length variants of CNF1 homologs. CNFx from E. coli strain GN02091 is the most distant from all other members of the CNF family with 50%-55% sequence identity at the protein level and 0.45-0.52 nucleotide substitutions per site at the DNA level. CNFx modifies RhoA, Rac1, and Cdc42, and like CNF1, activates downstream SRE-dependent mitogenic signaling pathways in human HEK293T cells, but at a 1,000-fold higher EC50 value. Unlike other previously characterized CNF toxins, CNFx modifies Rho proteins primarily through transglutamination, as evidenced by gel-shift assay and confirmed by MALDI mass spectral analysis, when coexpressed with Rho-protein substrates in E. coli BL21 cells or through direct treatment of HEK293T cells. A comparison of CNF1 and CNFx sequences identified two critical active-site residues corresponding to positions 832 and 862 in CNF1. Reciprocal site-specific mutations at these residues in each toxin revealed hierarchical rules that define the preference for deamidase versus a transglutaminase activity in CNFs. An additional unique Cys residue at the C-terminus of CNFx was also discovered to be critical for retarding cargo delivery.IMPORTANCECytotoxic necrotizing factor (CNF) toxins not only play important virulence roles in pathogenic E. coli and other bacterial pathogens, but CNF-like genes have also been found in an expanding number of genomes from clinical isolates. Harnessing the power of evolutionary relationships among the CNF toxins enabled the deciphering of the hierarchical active-site determinants that define whether they modify their Rho GTPase substrates through deamidation or transglutamination. With our finding that a distant CNF variant (CNFx) unlike other known CNFs predominantly transglutaminates its Rho GTPase substrates, the paradigm of "CNFs deamidate and DNTs transglutaminate" could finally be attributed to two critical amino acid residues within the active site other than the previously identified catalytic Cys-His dyad residues. The significance of our approach and research findings is that they can be applied to deciphering enzyme reaction determinants and substrate specificities for other bacterial proteins in the development of precision therapeutic strategies.