Identification and characterization of the capsule depolymerase Dpo27 from phage IME-Ap7 specific to Acinetobacter pittii.

Among the Acinetobacter genus, Acinetobacter pittii stands out as an important opportunistic infection causative agent commonly found in hospital settings, which poses a serious threat to human health. Recently, the high prevalence of carbapenem-resistant A. pittii isolates has created significant therapeutic challenges for clinicians. Bacteriophages and their derived enzymes are promising therapeutic alternatives or adjuncts to antibiotics effective against multidrug-resistant bacterial infections. However, studies investigating the depolymerases specific to A. pittii strains are scarce. In this study, we identified and characterized a capsule depolymerase, Dpo27, encoded by the bacteriophage IME-Ap7, which targets A. pittii. A total of 23 clinical isolates of Acinetobacter spp. were identified as A. pittii (21.91%, 23/105), and seven A. pittii strains with various K locus (KL) types (KL14, KL32, KL38, KL111, KL163, KL207, and KL220) were used as host bacteria for phage screening. The lytic phage IME-Ap7 was isolated using A. pittii 7 (KL220) as an indicator bacterium and was observed for depolymerase activity. A putative tail fiber gene encoding a polysaccharide-degrading enzyme (Dpo27) was identified and expressed. The results of the modified single-spot assay showed that both A. pittii 7 and 1492 were sensitive to Dpo27, which was assigned the KL220 type. After incubation with Dpo27, A. pittii strain was susceptible to killing by human serum; moreover, the protein displayed no hemolytic activity against erythrocytes. Furthermore, the protein exhibited sustained activity across a wide pH range (5.0-10.0) and at temperatures between 20 and 50°C. In summary, the identified capsule depolymerase Dpo27 holds promise as an alternative treatment for combating KL220-type A. pittii infections.

Coding genomes with gapped pattern graph convolutional network.

MOTIVATION: Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets. However, the highly variable lengths of genome sequences severely impair the presentation of sequences as input to the neural network. Genetic variations further complicate tasks that involve sequence comparison or alignment. RESULTS: Inspired by the theory and applications of "spaced seeds," we propose a graph representation of genome sequences called "gapped pattern graph." These graphs can be transformed through a Graph Convolutional Network to form lower-dimensional embeddings for downstream tasks. On the basis of the gapped pattern graphs, we implemented a neural network model and demonstrated its performance on diverse tasks involving microbe and mammalian genome data. Our method consistently outperformed all the other state-of-the-art methods across various metrics on all tasks, especially for the sequences with limited homology to the training data. In addition, our model was able to identify distinct gapped pattern signatures from the sequences. AVAILABILITY AND IMPLEMENTATION: The framework is available at https://github.com/deepomicslab/GCNFrame.

Corrigendum: Genetic characteristics and integration specificity of Salmonella enterica temperate phages.

[This corrects the article DOI: 10.3389/fmicb.2023.1199843.].

mStrain: strain-level identification of Yersinia pestis using metagenomic data.

Motivation: High-resolution target pathogen detection using metagenomic sequencing data represents a major challenge due to the low concentration of target pathogens in samples. We introduced mStrain, a novel Yesinia pestis strain/lineage-level identification tool that utilizes metagenomic data. mStrain successfully identified Y. pestis at the strain/lineage level by extracting sufficient information regarding single-nucleotide polymorphisms (SNPs), which can therefore be an effective tool for identification and source tracking of Y. pestis based on metagenomic data during a plague outbreak. Definition: . Strain-level identification: Assigning the reads in the metagenomic sequencing data to an exactly known or most closely representative Y. pestis strain. Lineage-level identification: Assigning the reads in the metagenomic sequencing data to a specific lineage on the phylogenetic tree. canoSNPs: The unique and typical SNPs present in all representative strains. Ancestor/derived state: An SNP is defined as the ancestor state when consistent with the allele of Yersinia pseudotuberculosis strain IP32953; otherwise, the SNP is defined as the derived state. Availability and implementation: The code for running mStrain, the test dataset, and instructions for running the code can be found at the following GitHub repository: https://github.com/xwqian1123/mStrain.

Genomic diversity of Yersinia pestis from Yunnan Province, China, implies a potential common ancestor as the source of two plague epidemics.

Plague, caused by Yersinia pestis, is a zoonotic disease that can reemerge and cause outbreaks following decades of latency in natural plague foci. However, the genetic diversity and spread pattern of Y. pestis during these epidemic-silent cycles remain unclear. In this study, we analyze 356 Y. pestis genomes isolated between 1952 and 2016 in the Yunnan Rattus tanezumi plague focus, China, covering two epidemic-silent cycles. Through high-resolution genomic epidemiological analysis, we find that 96% of Y. pestis genomes belong to phylogroup 1.ORI2 and are subdivided into two sister clades (Sublineage1 and Sublineage2) characterized by different temporal-spatial distributions and genetic diversity. Most of the Sublineage1 strains are isolated from the first epidemic-silent cycle, while Sublineage2 strains are predominantly from the second cycle and revealing a west to east spread. The two sister clades evolved in parallel from a common ancestor and independently lead to two separate epidemics, confirming that the pathogen responsible for the second epidemic following the silent interval is not a descendant of the causative strain of the first epidemic. Our results provide a mechanism for defining epidemic-silent cycles in natural plague foci, which is valuable in the prevention and control of future plague outbreaks.

Genomic epidemiological analysis of county-scale Yersinia pestis spread pattern over 50 years in a Southwest Chinese prefecture.

Plague, one of the most devastating infectious diseases in human history, is caused by the bacterium Yersinia pestis. Since the 1950s, the Dehong Dai-Jingpo Autonomous Prefecture (DH) in Yunnan Province, China, has recorded plague outbreaks that have resulted in 1,153 human cases and 379 deaths. The genetic diversity and transmission characteristics of Y. pestis strains in this region remain unknown. Here, we performed high-resolution genomic epidemiological analysis of 175 Y. pestis strains isolated from five counties and 19 towns in DH between 1953 and 2007. Phylogenetic analysis revealed that most DH strains were located in lineage 1.ORI2, which could be further subdivided into seven sub-phylogroups (SPG1-SPG7). The dominant sub-phylogroups of Y. pestis in DH varied during different periods and presented a population shift. Genomic evidence showed that plague might have emerged from the southwest of DH (e.g., Longchuan or Ruili counties) or its bordering countries, and subsequently spread to the northeast in multiple waves between 1982 and 2007. Our study infers a fine-scale phylogeny and spread pattern of the DH Y. pestis population, which extends our knowledge regarding its genetic diversity and provides clues for the future prevention and control of plague in this region.

Genetic characteristics and integration specificity of Salmonella enterica temperate phages.

Introduction: Temperate phages can engage in the horizontal transfer of functional genes to their bacterial hosts. Thus, their genetic material becomes an intimate part of bacterial genomes and plays essential roles in bacterial mutation and evolution. Specifically, temperate phages can naturally transmit genes by integrating their genomes into the bacterial host genomes via integrases. Our previous study showed that Salmonella enterica contains the largest number of temperate phages among all publicly available bacterial species. S. enterica is an important pathogen that can cause serious systemic infections and even fatalities. Methods: Initially, we extracted all S. enterica temperate phages from the extensively developed temperate phage database established in our previous study. Subsequently, we conducted an in-depth analysis of the genetic characteristics and integration specificity exhibited by these S. enterica temperate phages. Results: Here we identified 8,777 S. enterica temperate phages, all of which have integrases in their genomes. We found 491 non-redundant S. enterica temperate phage integrases (integrase entries). S. enterica temperate phage integrases were classified into three types: intA, intS, and phiRv2. Correlation analysis showed that the sequence lengths of S. enterica integrase and core regions of attB and attP were strongly correlated. Further phylogenetic analysis and taxonomic classification indicated that both the S. enterica temperate phage genomes and the integrase gene sequences were of high diversities. Discussion: Our work provides insight into the essential integration specificity and genetic diversity of S. enterica temperate phages. This study paves the way for a better understanding of the interactions between phages and S. enterica. By analyzing a large number of S. enterica temperate phages and their integrases, we provide valuable insights into the genetic diversity and prevalence of these elements. This knowledge has important implications for developing targeted therapeutic interventions, such as phage therapy, to combat S. enterica infections. By harnessing the lytic capabilities of temperate phages, they can be engineered or utilized in phage cocktails to specifically target and eradicate S. enterica strains, offering an alternative or complementary approach to traditional antibiotic treatments. Our study has implications for public health and holds potential significance in combating clinical infections caused by S. enterica.

Transcriptome sequencing and experiments reveal the effect of formyl peptide receptor 2 on liver homeostasis.

BACKGROUND: Formyl peptide receptor 2 (Fpr2) is an important receptor in host resistance to bacterial infections. In previous studies, we found that the liver of Fpr2-/- mice is the most severely damaged target organ in bloodstream infections, although the reason for this is unclear. AIM: To investigate the role of Fpr2 in liver homeostasis and host resistance to bacterial infections. METHODS: Transcriptome sequencing was performed on the livers of Fpr2-/- and wild-type (WT) mice. Differentially expressed genes (DEGs) were identified in the Fpr2-/- and WT mice, and the biological functions of DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) en-richment analysis. Quantitative real time-polymerase chain reaction (qRT-PCR) and western blot (WB) analyses were used to further validate the expression levels of differential genes. Cell counting kit-8 assay was employed to investigate cell survival. The cell cycle detection kit was used to measure the distribution of cell cycles. The Luminex assay was used to analyze cytokine levels in the liver. The serum biochemical indices and the number of neutrophils in the liver were measured, and hepatic histopathological analysis was performed. RESULTS: Compared with the WT group, 445 DEGs, including 325 upregulated genes and 120 downregulated genes, were identified in the liver of Fpr2-/- mice. The enrichment analysis using GO and KEGG showed that these DEGs were mainly related to cell cycle. The qRT-PCR analysis confirmed that several key genes (CycA, CycB1, Cdc20, Cdc25c, and Cdk1) involved in the cell cycle had significant changes. The WB analysis confirmed a decrease in the expression of CDK1 protein. WRW4 (an antagonist of Fpr2) could inhibit the proliferation of HepG2 cells in a concentration dependent manner, with an increase in the number of cells in the G0/G1 phase, and a decrease in the number of cells in the S phase. Serum alanine aminotransferase levels increased in Fpr2-/- mice. The Luminex assay measurements showed that interleukin (IL)-10 and chemokine (C-X-C motif) ligand (CXCL)-1 levels were significantly reduced in the liver of Fpr2-/- mice. There was no difference in the number of neutrophils, serum C-reactive protein levels, and liver pathology between WT and Fpr2-/- mice. CONCLUSION: Fpr2 participates in the regulation of cell cycle and cell proliferation, and affects the expression of IL-10 and CXCL-1, thus playing an important protective role in maintaining liver homeostasis.

Vibrio parahaemolyticus from Migratory Birds in China Carries an Extra Copy of tRNA-Gly and Plasmid-Mediated Quinolone Resistance Gene qnrD.

Vibrio parahaemolyticus is a marine bacterium coming from estuarine environments, where the migratory birds can easily be colonized by V. parahaemolyticus. Migratory birds may be important reservoirs of V. parahaemolyticus by growth and re-entry into the environment. To further explore the spreading mechanism of V. parahaemolyticus among marine life, human beings, and migratory birds, we aimed to investigate the characteristics of the genetic diversity, antimicrobial resistance, virulence genes, and a potentially informative gene marker of V. parahaemolyticus isolated from migratory birds in China. This study recovered 124 (14.55%) V. parahaemolyticus isolates from 852 fecal and environmental (water) samples. All of the 124 strains were classified into 85 known sequence types (STs), of which ST-2738 was most frequently identified. Analysis of the population structure using whole-genome variation of the 124 isolates illustrated that they grouped into 27 different clonal groups (CGs) belonging to the previously defined geographical populations VppX and VppAsia. Even though these genomes have high diversity, an extra copy of tRNA-Gly was presented in all migratory bird-carried V. parahaemolyticus isolates, which could be used as a potentially informative marker of the V. parahaemolyticus strains derived from birds. Antibiotic sensitivity experiments revealed that 47 (37.10%) isolates were resistant to ampicillin. Five isolates harbored the plasmid-mediated quinolone resistance (PMQR) gene qnrD, which has not previously been identified in this species. The investigation of antibiotic resistance provides the basic knowledge to further evaluate the risk of enrichment and reintroduction of pathogenic V. parahaemolyticus strains in migratory birds. IMPORTANCE The presence of V. parahaemolyticus in migratory birds' fecal samples implies that the human pathogenic V. parahaemolyticus strains may also potentially infect birds and thus pose a risk for zoonotic infection and food safety associated with re-entry into the environment. Our study firstly highlights the extra copy of tRNA as a potentially informative marker for identifying the bird-carried V. parahaemolyticus strains. Also, we firstly identify the plasmid-mediated quinolone resistance (PMQR) gene qnrD in V. parahaemolyticus. To further evaluate the risk of enrichment and reintroduction of pathogenic strains carried by migratory birds, we suggest conducting estuarine environmental surveillance to monitor the antibiotic resistance and virulence factors of bird-carried V. parahaemolyticus isolates.

Detection of Burkholderia pseudomallei with CRISPR-Cas12a based on specific sequence tags.

Melioidosis is a bacterial infection caused by Burkholderia pseudomallei (B. pseudomallei), posing a significant threat to public health. Rapid and accurate detection of B. pseudomallei is crucial for preventing and controlling melioidosis. However, identifying B. pseudomallei is challenging due to its high similarity to other species in the same genus. To address this issue, this study proposed a dual-target method that can specifically identify B. pseudomallei in less than 40 min. We analyzed 1722 B. pseudomallei genomes to construct large-scale pan-genomes and selected specific sequence tags in their core genomes that effectively distinguish B. pseudomallei from its closely related species. Specifically, we selected two specific tags, LC1 and LC2, which we combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated proteins (Cas12a) system and recombinase polymerase amplification (RPA) pre-amplification. Our analysis showed that the dual-target RPA-CRISPR/Cas12a assay has a sensitivity of approximately 0.2 copies/reaction and 10 fg genomic DNA for LC1, and 2 copies/reaction and 20 fg genomic DNA for LC2. Additionally, our method can accurately and rapidly detect B. pseudomallei in human blood and moist soil samples using the specific sequence tags mentioned above. In conclusion, the dual-target RPA-CRISPR/Cas12a method is a valuable tool for the rapid and accurate identification of B. pseudomallei in clinical and environmental samples, aiding in the prevention and control of melioidosis.

Population genomics implies potential public health risk of two non-toxigenic Vibrio cholerae lineages.

Diarrheal cases caused by non-toxigenic Vibrio cholerae have been reported globally. Lineages L3b and L9, characterized as ctxAB-negative and tcpA-positive (CNTP), pose the highest risk and have caused long-term epidemics in different regions worldwide. From 2001 to 2018, two waves (2001-2012 and 2013-2018) of epidemic caused by non-toxigenic V. cholerae occurred in the developed city of Hangzhou, China. In this study, through the integrated analysis of 207 genomes of Hangzhou isolates from these two waves (119 and 88) and 1573 publicly available genomes, we showed that L3b and L9 lineages together caused the second wave as had happened in the first wave, but the dominant lineage shifted from L3b (first wave: 69%) to L9 (second wave: 50%). We further found that the genotype of a key virulence gene, tcpF, in the L9 lineage during the second wave shifted to type I, which may have enhanced bacterial colonization in humans and potentially promoted the pathogenic lineage shift. Moreover, we found that 21% of L3b and L9 isolates had changed to predicted cholera toxin producers, providing evidence that gain of complete CTXφ-carrying ctxAB genes, rather than ctxAB gain in pre-CTXφ-carrying isolates, led to the transition. Taken together, our findings highlight the possible public health risk associated with L3b and L9 lineages due to their potential to cause long-term epidemics and turn into high-virulent cholera toxin producers, which necessitates a more comprehensive and unbiased sampling in further disease control efforts.

On triangle inequalities of correlation-based distances for gene expression profiles.

BACKGROUND: Distance functions are fundamental for evaluating the differences between gene expression profiles. Such a function would output a low value if the profiles are strongly correlated-either negatively or positively-and vice versa. One popular distance function is the absolute correlation distance, [Formula: see text], where [Formula: see text] is similarity measure, such as Pearson or Spearman correlation. However, the absolute correlation distance fails to fulfill the triangle inequality, which would have guaranteed better performance at vector quantization, allowed fast data localization, as well as accelerated data clustering. RESULTS: In this work, we propose [Formula: see text] as an alternative. We prove that [Formula: see text] satisfies the triangle inequality when [Formula: see text] represents Pearson correlation, Spearman correlation, or Cosine similarity. We show [Formula: see text] to be better than [Formula: see text], another variant of [Formula: see text] that satisfies the triangle inequality, both analytically as well as experimentally. We empirically compared [Formula: see text] with [Formula: see text] in gene clustering and sample clustering experiment by real-world biological data. The two distances performed similarly in both gene clustering and sample clustering in hierarchical clustering and PAM (partitioning around medoids) clustering. However, [Formula: see text] demonstrated more robust clustering. According to the bootstrap experiment, [Formula: see text] generated more robust sample pair partition more frequently (P-value [Formula: see text]). The statistics on the time a class "dissolved" also support the advantage of [Formula: see text] in robustness. CONCLUSION: [Formula: see text], as a variant of absolute correlation distance, satisfies the triangle inequality and is capable for more robust clustering.

HyperVR: a hybrid deep ensemble learning approach for simultaneously predicting virulence factors and antibiotic resistance genes.

Infectious diseases emerge unprecedentedly, posing serious challenges to public health and the global economy. Virulence factors (VFs) enable pathogens to adhere, reproduce and cause damage to host cells, and antibiotic resistance genes (ARGs) allow pathogens to evade otherwise curable treatments. Simultaneous identification of VFs and ARGs can save pathogen surveillance time, especially in situ epidemic pathogen detection. However, most tools can only predict either VFs or ARGs. Few tools that predict VFs and ARGs simultaneously usually have high false-negative rates, are sensitive to the cutoff thresholds and can only identify conserved genes. For better simultaneous prediction of VFs and ARGs, we propose a hybrid deep ensemble learning approach called HyperVR. By considering both best hit scores and statistical gene sequence patterns, HyperVR combines classical machine learning and deep learning to simultaneously and accurately predict VFs, ARGs and negative genes (neither VFs nor ARGs). For the prediction of individual VFs and ARGs, in silico spike-in experiment (the VFs and ARGs in real metagenomic data), and pseudo-VFs and -ARGs (gene fragments), HyperVR outperforms the current state-of-the-art prediction tools. HyperVR uses only gene sequence information without strict cutoff thresholds, hence making prediction straightforward and reliable.

Development and application of DETECTR-based rapid detection for pathogenic Bacillusanthracis.

Bacillus anthracis (B. anthracis) is a gram-positive bacterium responsible for the acute disease anthrax. Rapid and reliable identification of pathogenic B. anthracis is important in the detection of natural infectious disease cases or bio-threats. Herein, a DNA endonuclease targeted CRISPR trans reporter (DETECTR) detection platform based on recombinase polymerase amplification (RPA) was studied. The DETECTR system targeted three sequences from B. anthracis (the BA_5345 chromosomal specific marker, the protective antigen gene pag A from pXO1 plasmid and the capsule-biosynthesis-related gene cap A from pXO2 plasmid). We developed a rapid (<40 min), easy-to-implement and accurate identification method for of B. anthracis nucleic acid with near two-copies sensitivity. The combination of tripartite primer sets is effective for the reliable identification of B. anthracis but also for fast screening of pathogenic strains. More importantly, DETECTR correctly detected simulated clinical blood samples and firstly detected positive samples collected from the location of world War-II site, preserved at north-east China (45°36'55.940″ N, 126°38'33.738″ E) with high sensitivity and specificity. Our study provides insight into the DETECTR-based detection of B. anthracis. We present a novel screening and diagnostic option for pathogenic B. anthracis that can be performed on a user-friendly portable device. Based on its proven reliability, sensitivity, specificity and simplicity, our proposed method can be readily adapted to detect pathogenic B. anthracis, anthrax and biothreats.

Mining bacterial NGS data vastly expands the complete genomes of temperate phages.

Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to their lysogenicity, curbing their identification and characterization. Existing bioinformatics tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes. This study proposes a novel computational temperate phage detection method (TemPhD) mining both the integrated active prophages and their spontaneously induced forms (temperate phages) from next-generation sequencing raw data. Applying the method to the available dataset resulted in 192 326 complete temperate phage genomes with different host species, expanding the existing number of complete temperate phage genomes by more than 100-fold. The wet-lab experiments demonstrated that TemPhD can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites, outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the microbial evolution by (i) cross-infecting different bacterial host species; (ii) transferring antibiotic resistance and virulence genes and (iii) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensively complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.

Characterization and Genomic Analysis of Bacteriophage vB_KpnM_IME346 Targeting Clinical Klebsiella pneumoniae Strain of the K63 Capsular Type.

A Klebsiella pneumoniae bacteriophage (vB_KpnM_IME346) was isolated from a hospital sewage sample. This bacteriophage specifically infects a clinical K. pneumoniae strain with a K63 capsular polysaccharide structure. The phage genome was evaluated by next-generation sequencing, which revealed a linear double-stranded DNA genome consisting of 49,482 base pairs with a G+C content of 49.1%. The latent period of vB_KpnM_IME346 was shown to be 20 min, and the burst size was 25-30 pfu (plaque-forming units)/infected cell. Transmission electron microscopy and phylogenetic analysis showed that the JD001-like phage belongs to the genus Jedunavirus of the family Myoviridae. The newly isolated vB_KpnM_IME346 shows infectivity in the clinical host K. pneumoniae KP576 strain, indicating that it is a promising alternative to antibacterial agents for removing K. pneumoniae from patients.

Small Insertions and Deletions Drive Genomic Plasticity during Adaptive Evolution of Yersinia pestis.

The life cycle of Yersinia pestis has changed a lot to adapt to flea-borne transmission since it evolved from an enteric pathogen, Yersinia pseudotuberculosis. Small insertions and deletions (indels), especially frameshift mutations, can have major effects on phenotypes and contribute to virulence and host adaptation through gene disruption and inactivation. Here, we analyzed 365 Y. pestis genomes and identified 2,092 genome-wide indels on the core genome. As recently reported in Mycobacterium tuberculosis, we also detected "indel pockets" in Y. pestis, with average complexity scores declining around indel positions, which we speculate might also exist in other prokaryotes. Phylogenic analysis showed that indel-based phylogenic tree could basically reflect the phylogenetic relationships of major phylogroups in Y. pestis, except some inconsistency around the Big Bang polytomy. We observed 83 indels arising in the trunk of the phylogeny, which played a role in accumulation of pseudogenes related to key metabolism and putatively pathogenicity. We also discovered 32 homoplasies at the level of phylogroups and 7 frameshift scars (i.e., disrupted reading frame being rescued by a second frameshift). Additionally, our analysis showed evidence of parallel evolution at the level of genes, with sspA, rpoS, rnd, and YPO0624, having enriched mutations in Brazilian isolates, which might be advantageous for Y. pestis to cope with fluctuating environments. The diversified selection signals observed here demonstrates that indels are important contributors to the adaptive evolution of Y. pestis. Meanwhile, we provide potential targets for further exploration, as some genes/pseudogenes with indels we focus on remain uncharacterized. IMPORTANCE Yersinia pestis, the causative agent of plague, is a highly pathogenic clone of Yersinia pseudotuberculosis. Previous genome-wide SNP analysis provided few adaptive signatures during its evolution. Here by investigating 365 public genomes of Y. pestis, we give a comprehensive overview of general features of genome-wide indels on the core genome and their roles in Y. pestis evolution. Detection of "indel pockets," with average complexity scores declining around indel positions, in both Mycobacterium tuberculosis and Y. pestis, gives us a clue that this phenomenon might appear in other bacterial genomes. Importantly, the identification of four different forms of selection signals in indels would improve our understanding on adaptive evolution of Y. pestis, and provide targets for further physiological mechanism researches of this pathogen. As evolutionary research based on genome-wide indels is still rare in bacteria, our study would be a helpful reference in deciphering the role of indels in other species.

Genomic Epidemiology and Antimicrobial Susceptibility Profile of Enterotoxigenic Escherichia coli From Outpatients With Diarrhea in Shenzhen, China, 2015-2020.

Enterotoxigenic Escherichia coli (ETEC) is the leading cause of severe diarrhea in children and the most common cause of diarrhea in travelers. However, most ETEC infections in Shenzhen, China were from indigenous adults. In this study, we characterized 106 ETEC isolates from indigenous outpatients with diarrhea (77% were adults aged >20 years) in Shenzhen between 2015 and 2020 by whole-genome sequencing and antimicrobial susceptibility testing. Shenzhen ETEC isolates showed a remarkable high diversity, which belonged to four E. coli phylogroups (A: 71%, B1: 13%, E: 10%, and D: 6%) and 15 ETEC lineages, with L11 (25%, O159:H34/O159:H43, ST218/ST3153), novel L2/4 (21%, O6:H16, ST48), and L4 (15%, O25:H16, ST1491) being major lineages. Heat-stable toxin (ST) was most prevalent (76%, STh: 60% STp: 16%), followed by heat-labile toxin (LT, 17%) and ST + LT (7%). One or multiple colonization factors (CFs) were identified in 68 (64%) isolates, with the common CFs being CS21 (48%) and CS6 (34%). Antimicrobial resistance mutation/gene profiles of genomes were concordant with the phenotype testing results of 52 representative isolates, which revealed high resistance rate to nalidixic acid (71%), ampicillin (69%), and ampicillin/sulbactam (46%), and demonstrated that the novel L2/4 was a multidrug-resistant lineage. This study provides novel insight into the genomic epidemiology and antimicrobial susceptibility profile of ETEC infections in indigenous adults for the first time, which further improves our understanding on ETEC epidemiology and has implications for the development of vaccine and future surveillance and prevention of ETEC infections.

Genetic diversity and transmission patterns of Burkholderia pseudomallei on Hainan island, China, revealed by a population genomics analysis.

Burkholderia pseudomallei is a Gram-negative soil-dwelling bacillus that causes melioidosis, a frequently fatal infectious disease, in tropical and subtropical regions. Previous studies have identified the overall genetic and evolutionary characteristics of B. pseudomallei on a global scale, including its origin and transmission routes. However, beyond its known hyperendemicity foci in northern Australia and Southeast Asia, the distribution and genetic characteristics of B. pseudomallei in most tropical regions remain poorly understood, including in southern China. Here, we sequenced the genomes of 122 B. pseudomallei strains collected from Hainan, an island in southern China, in 2002-2018, to investigate the population structure, relationships with global strains, local epidemiology, and virulence and antimicrobial-resistance factors. A phylogenetic analysis and hierarchical clustering divided the Hainan strains into nine phylogenic groups (PGs), 80 % of which were concentrated within five major groups (group 1: corresponding to minor sequence types [STs], 12.3 %; group 3: ST46 and ST50, 31.1 %; group 9: ST58, 13.1 %; group 11: ST55, 8.2 %; group 15: mainly ST658, 15.6%). A phylogenetic analysis that included global strains suggested that B. pseudomallei in Hainan originated from Southeast Asian countries, transmitted in multiple historical importation events. We also identified several mutual transmission events between Hainan and Southeast Asian countries in recent years, including three importation events from Thailand and Singapore to Hainan and three exportation events from Hainan to Singapore, Malaysia, and Taiwan island. A statistical analysis of the temporal distribution showed that the Hainan strains of groups 3, 9, and 15 have dominated the disease epidemic locally in the last 5 years. The spatial distribution of the Hainan strains demonstrated that some PGs are distributed in different cities on Hainan island, and by combining phylogenic and geographic distribution information, we detected 21 between-city transmission events, indicating its frequent local transmission. The detection of virulence factor genes showed that 56 % of the Hainan strains in group 1 encode a B. pseudomallei-specific adherence factor, boaB, confirming the specific pathogenic characteristics of the Hainan strains in group 1. An analysis of the antimicrobial-resistance potential of B. pseudomallei showed that various kinds of alterations were identified in clinically relevant antibiotic resistance factors, such as AmrR, PenA and PBP3, etc. Our results clarify the population structure, local epidemiology, and pathogenic characteristics of B. pseudomallei in Hainan, providing further insight into its regional and global transmission networks and improving our knowledge of its global phylogeography.