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At least 253 records · Page 14

Draft genome sequence of Pseudomonas extremaustralis strain USBA-GBX 515 isolated from Superparamo soil samples in Colombian Andes

Abstract Here we present the physiological features of Pseudomonas extremaustralis strain USBA-GBX-515 ( CMPUJU 515 ), isolated from soils in Superparamo ecosystems, > 4000 m.a.s.l, in the northern Andes of South America, as well as the thorough analysis of the draft genome. Strain USBA-GBX-515 is a Gram-negative rod shaped bacterium of 1.0–3.0 μm × 0.5–1 μm, motile and unable to form spores, it grows aerobically and cells show one single flagellum. Several genetic indices, the phylogenetic analysis of the 16S rRNA gene sequence and the phenotypic characterization confirmed that USBA-GBX-515 is a member of Pseudomonas genus and, the similarity of the 16S rDNA sequence was 100% with P. extremaustralis strain CT14–3 T . The draft genome of P. extremaustralis strain USBA-GBX-515 consisted of 6,143,638 Mb with a G + C content of 60.9 mol%. A total of 5665 genes were predicted and of those, 5544 were protein coding genes and 121 were RNA genes. The distribution of genes into COG functional categories showed that most genes were classified in the category of amino acid transport and metabolism (10.5%) followed by transcription (8.4%) and signal transduction mechanisms (7.3%). We performed experimental analyses of the lipolytic activity and results showed activity mainly on short chain fatty acids. The genome analysis demonstrated the existence of two genes, lip515A and est515A, related to a triacylglycerol lipase and carboxylesterase, respectively. Ammonification genes were also observed, mainly nitrate reductase genes. Genes related with synthesis of poly-hydroxyalkanoates (PHAs), especially poly-hydroxybutyrates (PHBs), were detected. The phaABC and phbABC operons also appeared complete in the genome. P. extremaustralis strain USBA-GBX-515 conserves the same gene organization of the type strain CT14–3 T . We also thoroughly analyzed the potential for production of secondary metabolites finding close to 400 genes in 32 biosynthetic gene clusters involved in their production.

16S rRNA↗

Rhesus macaque and mouse models for down-selecting circumsporozoite protein based malaria vaccines differ significantly in immunogenicity and functional outcomes

Background: Non-human primates, such as the rhesus macaques, are the preferred model for down-selecting human malaria vaccine formulations, but the rhesus model is expensive and does not allow for direct efficacy testing of human malaria vaccines. Transgenic rodent parasites expressing genes of human Plasmodium are now routinely used for efficacy studies of human malaria vaccines. Mice have however rarely predicted success in human malaria trials and there is scepticism whether mouse studies alone are sufficient to move a vaccine candidate into the clinic. Methods: A comparison of immunogenicity, fine-specificity and functional activity of two Alum-adjuvanted Plasmodium falciparum circumsporozoite protein (CSP)-based vaccines was conducted in mouse and rhesus models. One vaccine was a soluble recombinant protein (CSP) and the other was the same CSP covalently conjugated to the Qβ phage particle (Qβ-CSP). Results: Mice showed different kinetics of antibody responses and different sensitivity to the NANP-repeat and N-terminal epitopes as compared to rhesus. While mice failed to discern differences between the protective efficacy of CSP versus Qβ-CSP vaccine following direct challenge with transgenic Plasmodium berghei parasites, rhesus serum from the Qβ-CSP-vaccinated animals induced higher in vivo sporozoite neutralization activity. Conclusions: Despite some immunologic parallels between models, these data demonstrate that differences between the immune responses induced in the two models risk conflicting decisions regarding potential vaccine utility in humans. In combination with historical observations, the data presented here suggest that although murine models may be useful for some purposes, non-human primate models may be more likely to predict the human response to investigational vaccines.

60 APPLIED LIFE SCIENCES↗

Computation-guided optimization of split protein systems

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute, even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. Furthermore, this new technology will streamline the generation and use of split protein systems for diverse applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energetic Basis and Design of Enzyme Function Demonstrated Using GFP, an Excited-State Enzyme

We report the past decades have witnessed an explosion of de novo protein designs with a remarkable range of scaffolds. It remains challenging, however, to design catalytic functions that are competitive with naturally occurring counterparts as well as biomimetic or nonbiological catalysts. Although directed evolution often offers efficient solutions, the fitness landscape remains opaque. Green fluorescent protein (GFP), which has revolutionized biological imaging and assays, is one of the most redesigned proteins. While not an enzyme in the conventional sense, GFPs feature competing excited-state decay pathways with the same steric and electrostatic origins as conventional ground-state catalysts, and they exert exquisite control over multiple reaction outcomes through the same principles. Thus, GFP is an “excited-state enzyme”. Herein we show that rationally designed mutants and hybrids that contain environmental mutations and substituted chromophores provide the basis for a quantitative model and prediction that describes the influence of sterics and electrostatics on excited-state catalysis of GFPs. As both perturbations can selectively bias photoisomerization pathways, GFPs with fluorescence quantum yields (FQYs) and photoswitching characteristics tailored for specific applications could be predicted and then demonstrated. The underlying energetic landscape, readily accessible via spectroscopy for GFPs, offers an important missing link in the design of protein function that is generalizable to catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of condition-specific regulatory genes using machine learning

Recent advances in genomic technologies have generated data on large-scale protein–DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5–25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sas20 is a highly flexible starch-binding protein in the Ruminococcus bromii cell-surface amylosome

Ruminococcus bromii is a keystone species in the human gut that has the rare ability to degrade dietary resistant starch (RS). This bacterium secretes a suite of starch-active proteins that work together within larger complexes called amylosomes that allow R. bromii to bind and degrade RS. Starch adherence system protein 20 (Sas20) is one of the more abundant proteins assembled within amylosomes, but little could be predicted about its molecular features based on amino acid sequence. Here, we performed a structure–function analysis of Sas20 and determined that it features two discrete starch-binding domains separated by a flexible linker. We show that Sas20 domain 1 contains an N-terminal β-sandwich followed by a cluster of α-helices, and the nonreducing end of maltooligosaccharides can be captured between these structural features. Furthermore, the crystal structure of a close homolog of Sas20 domain 2 revealed a unique bilobed starch-binding groove that targets the helical α1,4-linked glycan chains found in amorphous regions of amylopectin and crystalline regions of amylose. Affinity PAGE and isothermal titration calorimetry demonstrated that both domains bind maltoheptaose and soluble starch with relatively high affinity (K d ≤ 20 μM) but exhibit limited or no binding to cyclodextrins. Finally, small-angle X-ray scattering analysis of the individual and combined domains support that these structures are highly flexible, which may allow the protein to adopt conformations that enhance its starch-targeting efficiency. Taken together, we conclude that Sas20 binds distinct features within the starch granule, facilitating the ability of R. bromii to hydrolyze dietary RS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural, Functional, and Immunogenic Insights on Cu,Zn Superoxide Dismutase Pathogenic Virulence Factors from Neisseria meningitidis and Brucella abortus

ABSTRACT Bacterial pathogens Neisseria meningitidis and Brucella abortus pose threats to human and animal health worldwide, causing meningococcal disease and brucellosis, respectively. Mortality from acute N. meningitidis infections remains high despite antibiotics, and brucellosis presents alimentary and health consequences. Superoxide dismutases are master regulators of reactive oxygen and general pathogenicity factors and are therefore therapeutic targets. Cu,Zn superoxide dismutases (SODs) localized to the periplasm promote survival by detoxifying superoxide radicals generated by major host antimicrobial immune responses. We discovered that passive immunization with an antibody directed at N. meningitidis SOD (NmSOD) was protective in a mouse infection model. To define the relevant atomic details and solution assembly states of this important virulence factor, we report high-resolution and X-ray scattering analyses of NmSOD and of SOD from B. abortus (BaSOD). The NmSOD structures revealed an auxiliary tetrahedral Cu-binding site bridging the dimer interface; mutational analyses suggested that this metal site contributes to protein stability, with implications for bacterial defense mechanisms. Biochemical and structural analyses informed us about electrostatic substrate guidance, dimer assembly, and an exposed C-terminal epitope in the NmSOD dimer. In contrast, the monomeric BaSOD structure provided insights for extending immunogenic peptide epitopes derived from the protein. These collective results reveal unique contributions of SOD to pathogenic virulence, refine predictive motifs for distinguishing SOD classes, and suggest general targets for antibacterial immune responses. The identified functional contributions, motifs, and targets distinguishing bacterial and eukaryotic SOD assemblies presented here provide a foundation for efforts to develop SOD-specific inhibitors of or vaccines against these harmful pathogens. IMPORTANCE By protecting microbes against reactive oxygen insults, SODs aid survival of many bacteria within their hosts. Despite the ubiquity and conservation of these key enzymes, notable species-specific differences relevant to pathogenesis remain undefined. To probe mechanisms that govern the functioning of Neisseria meningitidis and Brucella abortus SODs, we used X-ray structures, enzymology, modeling, and murine infection experiments. We identified virulence determinants common to the two homologs, assembly differences, and a unique metal reservoir within meningococcal SOD that stabilizes the enzyme and may provide a safeguard against copper toxicity. The insights reported here provide a rationale and a basis for SOD-specific drug design and an extension of immunogen design to target two important pathogens that continue to pose global health threats.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Persistent Protein Motions in a Rugged Energy Landscape Revealed by Normal Mode Ensemble Analysis

Proteins are allosteric machines that couple motions at distinct, often distant, sites to control biological function. Low-frequency structural vibrations are a mechanism of this long-distance connection and are often used computationally to predict correlations, but experimentally identifying the vibrations associated with specific motions has proved challenging. Spectroscopy is an ideal tool to explore these excitations, but measurements have been largely unable to identify important frequency bands. The result is at odds with some previous calculations and raises the question what methods could successfully characterize protein structural vibrations. Here we show the lack of spectral structure arises in part from the variations in protein structure as the protein samples the energy landscape. However, by averaging over the energy landscape as sampled using an aggregate 18.5 μs of all-atom molecular dynamics simulation of hen egg white lysozyme and normal-mode analyses, we find vibrations with large overlap with functional displacements are surprisingly concentrated in narrow frequency bands. These bands are not apparent in either the ensemble averaged vibrational density of states or isotropic absorption. However, in the case of the ensemble averaged anisotropic absorption, there is persistent spectral structure and overlap between this structure and the functional displacement frequency bands. We systematically lay out heuristics for calculating the spectra robustly, including the need for statistical sampling of the protein and inclusion of adequate water in the spectral calculation. The results show the congested spectrum of these complex molecules obscures important frequency bands associated with function and reveal a method to overcome this congestion by combining structurally sensitive spectroscopy with robust normal mode ensemble analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nesprin-2 epsilon: A novel nesprin isoform expressed in human ovary and Ntera-2 cells

Highlights: {yields} A novel epsilon isoform of nesprin-2 has been discovered. {yields} This 120 kDa protein was predicted by bioinformatic analysis, but has not previously been observed. {yields} It is the main isoform expressed in a teratocarcinoma cell line and is also found in ovary. {yields} Like other nesprins, it is located at the nuclear envelope. {yields} We suggest it may have a role in very early development or in some ovary-specific function. -- Abstract: The nuclear envelope-associated cytoskeletal protein, nesprin-2, is encoded by a large gene containing several internal promoters that produce shorter isoforms. In a study of Ntera-2 teratocarcinoma cells, a novel isoform, nesprin-2-epsilon, was found to be the major mRNA and protein product of the nesprin-2 gene. Its existence was predicted by bioinformatic analysis, but this is the first direct demonstration of both the mRNA and the 120 kDa protein which is located at the nuclear envelope. In a panel of 21 adult and foetal human tissues, the nesprin-2-epsilon mRNA was strongly expressed in ovary but was a minor isoform elsewhere. The expression pattern suggests a possible link with very early development and a likely physiological role in ovary.

60 APPLIED LIFE SCIENCES↗

Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery

Molecular recognition is fundamental in biology, underpinning intricate processes through specific protein–ligand interactions. This understanding is pivotal in drug discovery, yet traditional experimental methods face limitations in exploring the vast chemical space. Computational approaches, notably quantitative structure–activity/property relationship analysis, have gained prominence. Molecular fingerprints encode molecular structures and serve as property profiles, which are essential in drug discovery. While two-dimensional (2D) fingerprints are commonly used, three-dimensional (3D) structural interaction fingerprints offer enhanced structural features specific to target proteins. Machine learning models trained on interaction fingerprints enable precise binding prediction. Recent focus has shifted to structure-based predictive modeling, with machine-learning scoring functions excelling due to feature engineering guided by key interactions. Notably, 3D interaction fingerprints are gaining ground due to their robustness. Various structural interaction fingerprints have been developed and used in drug discovery, each with unique capabilities. This review recapitulates the developed structural interaction fingerprints and provides two case studies to illustrate the power of interaction fingerprint-driven machine learning. The first elucidates structure–activity relationships in β2 adrenoceptor ligands, demonstrating the ability to differentiate agonists and antagonists. The second employs a retrosynthesis-based pre-trained molecular representation to predict protein–ligand dissociation rates, offering insights into binding kinetics. Despite remarkable progress, challenges persist in interpreting complex machine learning models built on 3D fingerprints, emphasizing the need for strategies to make predictions interpretable. Binding site plasticity and induced fit effects pose additional complexities. Interaction fingerprints are promising but require continued research to harness their full potential.

3D structural interaction fingerprints↗

Exploring soybean metabolic pathways based on probabilistic graphical model and knowledge-based methods

Soybean (Glycine max) is a major source of vegetable oil and protein for both animal and human consumption. The completion of soybean genome sequence led to a number of transcriptomic studies (RNA-seq), which provide a resource for gene discovery and functional analysis. Several data-driven (e.g., based on gene expression data) and knowledge-based (e.g., predictions of molecular interactions) methods have been proposed and implemented. In order to better understand gene relationships and protein interactions, we applied probabilistic graphical methods, based on Bayesian network and knowledgebase constraints using gene expression data to reconstruct soybean metabolic pathways. The results show that this method can predict new relationships between genes, improving on traditional reference pathway maps.

54 ENVIRONMENTAL SCIENCES↗

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4)

Abstract The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

59 BASIC BIOLOGICAL SCIENCES↗

Complete genome sequence of the phenanthrene-degrading soil bacterium Delftia acidovorans Cs1-4

Polycyclic aromatic hydrocarbons (PAH) are ubiquitous environmental pollutants and microbial biodegradation is an important means of remediation of PAH-contaminated soil. Delftia acidovorans Cs1-4 (formerly Delftia sp. Cs1-4) was isolated by using phenanthrene as the sole carbon source from PAH contaminated soil in Wisconsin. Its full genome sequence was determined to gain insights into a mechanisms underlying biodegradation of PAH. Three genomic libraries were constructed and sequenced: an Illumina GAii shotgun library (916,416,493 reads), a 454 Titanium standard library (770,171 reads) and one paired-end 454 library (average insert size of 8 kb, 508,092 reads). The initial assembly contained 40 contigs in two scaffolds. The 454 Titanium standard data and the 454 paired end data were assembled together and the consensus sequences were computationally shredded into 2 kb overlapping shreds. Illumina sequencing data was assembled, and the consensus sequence was computationally shredded into 1.5 kb overlapping shreds. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks. A total of 182 additional reactions were needed to close gaps and to raise the quality of the finished sequence. The final assembly is based on 253.3 Mb of 454 draft data (averaging 38.4 X coverage) and 590.2 Mb of Illumina draft data (averaging 89.4 X coverage). The genome of strain Cs1-4 consists of a single circular chromosome of 6,685,842 bp (66.7 %G+C) containing 6,028 predicted genes; 5,931 of these genes were protein-encoding and 4,425 gene products were assigned to a putative function. Genes encoding phenanthrene degradation were localized to a 232 kb genomic island (termed the phn island), which contained near its 3’ end a bacteriophage P4-like integrase, an enzyme often associated with chromosomal integration of mobile genetic elements. Other biodegradation pathways reconstructed from the genome sequence included: benzoate (by the acetyl-CoA pathway), styrene, nicotinic acid (by the maleamate pathway) and the pesticides Dicamba and Fenitrothion. Lastly, determination of the complete genome sequence of D. acidovorans Cs1-4 has provided new insights the microbial mechanisms of PAH biodegradation that may shape the process in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Who Is Metabolizing What? Discovering Novel Biomolecules in the Microbiome and the Organisms Who Make Them

Even as the field of microbiome research has made huge strides in mapping microbial community composition in a variety of environments and organisms, explaining the phenotypic influences on the host by microbial taxa – both known and unknown – and their specific functions still remain major challenges. A pressing need is the ability to assign specific functions in terms of enzymes and small molecules to specific taxa or groups of taxa in the community. This knowledge will be crucial for advancing personalized therapies based on the targeted modulation of microbes or metabolites that have predictable outcomes to benefit the human host. This perspective article advocates for the combined use of standards-free metabolomics and activity-based protein profiling strategies to address this gap in functional knowledge in microbiome research via the identification of novel biomolecules and the attribution of their production to specific microbial taxa.

59 BASIC BIOLOGICAL SCIENCES↗

Possible Dynamically Gated Conductance along Heme Wires in Bacterial Multiheme Cytochromes

The staggered cross decaheme configuration of electron transfer co-factors in the outer-membrane cytochrome MtrF may serve as a prototype for conformationally-gated multi-heme electron transport. Derived from the bacterium Shewanella oneidensis, the staggered cross configuration reveals intersecting c-type octaheme and tetraheme “wires” containing thermodynamic “hills” and “valleys”, suggesting that the protein structure may include a dynamical mechanism for conductance and pathway switching depending on enzymatic functional need. Recent molecular simulations have established the pair-wise electronic couplings, redox potentials, and reorganization energies to predict the maximum conductance along the various heme wire pathways by sequential hopping of a single electron (PNAS (2014) 11,611-616). Here, we expand this information with classical molecular and statistical mechanics calculations of large-amplitude protein dynamics in MtrF, to address its potential to modulate pathway conductance, including assessment of the effect of the total charge state. Explicit solvent molecular dynamics simulations of fully oxidized and fully reduced MtrF employing ten independent 50-ns simulations at 300 K and 1 atm showed that reduced MtrF is more expanded and explores more conformational space than oxidized MtrF, and that heme reduction leads to increased heme solvent exposure. The slowest mode of collective decaheme motion is 90% similar between the oxidized and reduced states, and consists primarily of inter-heme separation with minor rotational contributions. The frequency of this motion is 1.7×107 s 1 for fully-oxidized and fully-reduced MtrF, respectively, slower than the downhill electron transfer rates between stacked heme pairs at the octaheme termini and faster than the electron transfer rates between parallel hemes in the tetraheme chain. This implies that MtrF uses slow conformational fluctuations to modulate electron flow along the octaheme pathway, apparently for the purpose of increasing the residence time of electrons on lowest potential hemes 4 and 9. This apparent gating mechanism should increase the success rate of electron transfer from MtrF to low potential environmental acceptors via these two solvent-exposed hemes.

c-type cytochromes, MtrF, Shewanella oneidensis, h↗

Enzyme property prediction using artificial intelligence

Artificial intelligence (AI)-driven enzyme property prediction enables rapid discovery and engineering of enzymes for a wide range of biotechnological and therapeutic applications. Here, we first introduce the key components in AI model development, including enzyme datasets, protein representation methods, and model architectures. We then highlight a variety of AI tools developed for the prediction of enzyme properties and functional annotations, including enzyme structure, kinetic parameters, substrate specificity, thermostability, solubility, Enzyme Commission number, and Gene Ontology term. Moreover, we describe representative downstream applications enabled by these AI tools. Finally, we discuss some challenges and opportunities as well as future prospects.

Yuan, Le [University of Illinois at Urbana-Champai↗

Supersize me: Cronobacter sakazakii phage GAP32

Cronobacter sakazakii is a Gram-negative pathogen found in milk-based formulae that causes infant meningitis. Bacteriophages have been proposed to control bacterial pathogens; however, comprehensive knowledge about a phage is required to ensure its safety before clinical application. We have characterized C. sakazakii phage vB{sub C}saM{sub G}AP32 (GAP32), which possesses the second largest sequenced phage genome (358,663 bp). A total of 571 genes including 545 protein coding sequences and 26 tRNAs were identified, thus more genes than in the smallest bacterium, Mycoplasma genitalium G37. BLASTP and HHpred searches, together with proteomic analyses reveal that only 23.9% of the putative proteins have defined functions. Some of the unique features of this phage include: a chromosome condensation protein, two copies of the large subunit terminase, a predicted signal-arrest-release lysin; and an RpoD-like protein, which is possibly involved in the switch from immediate early to delayed early transcription. Its closest relatives are all extremely large myoviruses, namely coliphage PBECO4 and Klebsiella phage vB{sub K}leM-RaK2, with whom it shares approximately 44% homologous proteins. Since the homologs are not evenly distributed, we propose that these three phages belong to a new subfamily. - Highlights: • Cronobacter sakazakii phage vB{sub C}saM{sub G}AP32 has a genome of 358,663 bp. • It encodes 545 proteins which is more than Mycoplasma genitalium G37. • It is a member of the Myoviridae. • It is peripherally related to coliphage PBECO4 and Klebsiella phage vB{sub K}leM-RaK2. • GAP32 encodes a chromosome condensation protein.

60 APPLIED LIFE SCIENCES↗

Dual Targeting Factors Are Required for LXG Toxin Export by the Bacterial Type VIIb Secretion System

Bacterial type VIIb secretion systems (T7SSb) are multisubunit integral membrane protein complexes found in Firmicutes that play a role in both bacterial competition and virulence by secreting toxic effector proteins. The majority of characterized T7SSb effectors adopt a polymorphic domain architecture consisting of a conserved N-terminal Leu-X-Gly (LXG) domain and a variable C-terminal toxin domain. Recent work has started to reveal the diversity of toxic activities exhibited by LXG effectors; however, little is known about how these proteins are recruited to the T7SSb apparatus. In this work, we sought to characterize genes encoding domains of unknown function (DUFs) 3130 and 3958, which frequently cooccur with LXG effector-encoding genes. Using coimmunoprecipitation-mass spectrometry analyses, in vitro copurification experiments, and T7SSb secretion assays, we found that representative members of these protein families form heteromeric complexes with their cognate LXG domain and in doing so, function as targeting factors that promote effector export. Additionally, an X-ray crystal structure of a representative DUF3958 protein, combined with predictive modeling of DUF3130 using AlphaFold2, revealed structural similarity between these protein families and the ubiquitous WXG100 family of T7SS effectors. Interestingly, we identified a conserved FxxxD motif within DUF3130 that is reminiscent of the YxxxD/E “export arm” found in mycobacterial T7SSa substrates and mutation of this motif abrogates LXG effector secretion. Overall, our data experimentally link previously uncharacterized bacterial DUFs to type VIIb secretion and reveal a molecular signature required for LXG effector export.

24 antibacterial toxins↗