F1ALA: ultrafast and memory-efficient ancestral lineage annotation applied to the huge SARS-CoV-2 phylogeny.

The unprecedentedly large size of the global SARS-CoV-2 phylogeny makes any computation on the tree difficult. Lineage identification (e.g. the PANGO nomenclature for SARS-CoV-2) and assignment are key to track the virus evolution. It requires annotating clade roots of lineages to unlabeled ancestral nodes in a phylogenetic tree. Then the lineage labels of descendant samples under these clade roots can be inferred to be the corresponding lineages. This is the ancestral lineage annotation problem, and matUtils (a package in pUShER) and PastML are commonly used methods. However, their computational tractability is a challenge and their accuracy needs further exploration in huge SARS-CoV-2 phylogenies. We have developed an efficient and accurate method, called "F1ALA", that utilizes the F1-score to evaluate the confidence with which a specific ancestral node can be annotated as the clade root of a lineage, given the lineage labels of a set of taxa in a rooted tree. Compared to these methods, F1ALA achieved roughly an order of magnitude faster yet with ∼12% of their memory usage when annotating 2277 PANGO lineages in a phylogeny of 5.26 million taxa. F1ALA allows real-time lineage tracking to be performed on a laptop computer. F1ALA outperformed matUtils (pUShER) with statistical significance, and had comparable accuracy to PastML in tests on empirical and simulated data. F1ALA enables a tree refinement by pruning taxa with inconsistent labels to their closest annotation nodes and re-inserting them back to the pruned tree to improve a SARS-CoV-2 phylogeny with both higher log-likelihood and lower parsimony score. Given the ultrafast speed and high accuracy, we anticipated that F1ALA will also be useful for large phylogenies of other viruses. Codes and benchmark datasets are publicly available at https://github.com/id-bioinfo/F1ALA.

Baseline Gut Microbiota Was Associated with Long-Term Immune Response at One Year Following Three Doses of BNT162b2.

BACKGROUND: This study explored neutralizing IgG antibody levels against COVID-19 decline over time post-vaccination. We conducted this prospective cohort study to investigate the function of gut microbiota in the host immune response following three doses of BNT162b2. METHODS: Subjects who received three doses of BNT162b2 were recruited from three centers in Hong Kong. Blood samples were obtained before the first dose and at the one-year timepoint for IgG ELISA to determine the level of neutralizing antibody (NAb). The primary outcome was a high immune response (NAb > 600 AU/mL). We performed shotgun DNA metagenomic sequencing on baseline fecal samples to identify bacterial species and metabolic pathways associated with high immune response using linear discriminant analysis effect size analysis. RESULTS: A total of 125 subjects were recruited (median age: 52 years [IQR: 46.2-59.0]; male: 43 [34.4%]), and 20 were regarded as low responders at the one-year timepoint. Streptococcus parasanguinis (log10LDA score = 2.38, p = 0.003; relative abundance of 2.97 × 10-5 vs. 0.03%, p = 0.001), Bacteroides stercoris (log10LDA score = 4.29, p = 0.024; relative abundance of 0.14% vs. 2.40%, p = 0.014) and Haemophilus parainfluenzae (log10LDA score = 2.15, p = 0.022; relative abundance of 0.01% vs. 0, p = 0.010) were enriched in low responders. Bifidobacterium pseudocatenulatum (log10LDA score = 2.99, p = 0.048; relative abundance of 0.09% vs. 0.36%, p = 0.049) and Clostridium leptum (log10LDA score = 2.38, p = 0.014; relative abundance of 1.2 × 10-5% vs. 0, p = 0.044) were enriched in high responders. S. parasanguinis was negatively correlated with the superpathway of pyrimidine ribonucleotides de novo biosynthesis (log10LDA score = 2.63), which contributes to inflammation and antibody production. H. parainfluenzae was positively correlated with pathways related to anti-inflammatory processes, including the superpathway of histidine, purine, and pyrimidine biosynthesis (log10LDA score = 2.14). CONCLUSION: Among three-dose BNT162b2 recipients, S. parasanguinis, B. stercoris and H. parainfluenzae were associated with poorer immunogenicity at one year, while B. pseudocatenulatum and C. leptum was associated with a better response.

Does repetitive transcranial magnetic stimulation have a beneficial effect on improving unilateral spatial neglect caused by stroke? A meta-analysis.

This review aimed to assess the effect of repetitive transcranial magnetic stimulation (rTMS) in improving post-stroke unilateral spatial neglect (USN) using a meta-analysis. Further, we aimed to identify any association between rTMS parameters, patient demographics, and treatment effect sizes using subgroup analyses and meta-regression. A literature search was conducted through four databases from inception to March 6, 2024, to retrieve all relevant controlled trials investigating the effects of rTMS on symptoms of USN in post-stroke patients. Overall, rTMS significantly improved post-stroke USN, as measured by the line bisection test (Hedges' g = - 1.301, p < 0.0001), the cancelation test (Hedge's g = - 1.512, p < 0.0001), and the Catherine Bergego Scale (Hedges'g = - 0.770, p < 0.0001), compared to sham stimulation. Subgroup analysis found that generally larger effect sizes following excitatory rTMS across several outcome measures, indicating that excitatory rTMS on the ipsilesional hemisphere may be more effective than inhibitory rTMS on the contralesional hemisphere in ameliorating neglect symptoms. Meta-regression analysis of the line bisection test showed a significant difference in the chronicity of stroke patients, suggesting that rTMS may be more effective for USN in patients at the acute stage (within 3 months since stroke) than in those at the post-acute stage (p = 0.035). In conclusion, rTMS appears to be effective in promoting recovery from post-stroke USN. Excitatory protocols and early intervention may enhance recovery outcomes for neglect behaviors in post-stroke survivors.

Challenges for ticks and tick-borne diseases research in Southeast Asia: Insight from the first international symposium in Cambodia.

BACKGROUND: Ticks, as critical vectors of a variety of pathogens, pose a significant public health challenge globally. In Southeast Asia (SEA), ticks are responsible for transmitting a diverse array of pathogens affecting humans and animals. The geographical and ecological diversity of SEA provides a unique environment that supports a wide range of tick species, which complicates the management and study of tick-borne diseases (TBDs). METHODOLOGY/PRINCIPAL FINDINGS: This article synthesizes findings from the first international symposium on ticks and TBDs in Southeast Asia, held in Phnom Penh on June 22 and 23, 2023. It highlights regional efforts to understand tick ecology and pathogen transmission. This paper proposes to present a summary of the various presentations given during the symposium following 3 main parts. The first one is devoted to the state of knowledge regarding ticks and TBDs in SEA countries, with presentations from 6 different countries, namely Cambodia, Indonesia, Laos, Malaysia, Thailand, and Vietnam. The second part focuses on the development of new research approaches on tick-borne pathogens (TBPs) and TBDs. The last part is a summary of the round table discussion held on the final day, with the aim of defining the most important challenges and recommendations for researches on TBP and TBD in the SEA region. CONCLUSIONS/SIGNIFICANCE: Key topics discussed include advancements in diagnostic tools, such as MALDI-TOF MS and proteomics, and the development of sustainable strategies for tick management and disease prevention. The symposium facilitated the exchange of knowledge and collaborative networks among experts from various disciplines, promoting a unified approach to tackling TBDs in the region. The symposium underscored the need for enhanced surveillance, diagnostics, and inter-regional cooperation to manage the threat of TBDs effectively. Recommendations include the establishment of a regional database for tick identification and the expansion of vector competence studies. These initiatives are crucial for developing targeted interventions and understanding the broader implications of climate change and urbanization on the prevalence of TBDs.

Proposal for a Global Classification and Nomenclature System for A/H9 Influenza Viruses.

Influenza A/H9 viruses circulate worldwide in wild and domestic avian species, continuing to evolve and posing a zoonotic risk. A substantial increase in human infections with A/H9N2 subtype avian influenza viruses (AIVs) and the emergence of novel reassortants carrying A/H9N2-origin internal genes has occurred in recent years. Different names have been used to describe the circulating and emerging A/H9 lineages. To address this issue, an international group of experts from animal and public health laboratories, endorsed by the WOAH/FAO Network of Expertise on Animal Influenza, has created a practical lineage classification and nomenclature system based on the analysis of 10,638 hemagglutinin sequences from A/H9 AIVs sampled worldwide. This system incorporates phylogenetic relationships and epidemiologic characteristics designed to trace emerging and circulating lineages and clades. To aid in lineage and clade assignment, an online tool has been created. This proposed classification enables rapid comprehension of the global spread and evolution of A/H9 AIVs.

Ecoclimate drivers shape virome diversity in a globally invasive tick species.

Spillovers of viruses from animals to humans occur more frequently under warmer conditions, particularly arboviruses. The invasive tick species Haemaphysalis longicornis, the Asian longhorned tick, poses a significant public health threat due to its global expansion and its potential to carry a wide range of pathogens. We analyzed meta-transcriptomic data from 3595 adult H. longicornis ticks collected between 2016 and 2019 in 22 provinces across China encompassing diverse ecological conditions. Generalized additive modeling revealed that climate factors exerted a stronger influence on the virome of H. longicornis than other ecological factors, such as ecotypes, distance to coastline, animal host, tick gender, and antiviral immunity. To understand how climate changes drive the tick virome, we performed a mechanistic investigation using causality inference with emphasis on the significance of this process for public health. Our findings demonstrated that higher temperatures and lower relative humidity/precipitation contribute to variations in animal host diversity, leading to increased diversity of the tick virome, particularly the evenness of vertebrate-associated viruses. These findings may explain the evolution of tick-borne viruses into generalists across multiple hosts, thereby increasing the probability of spillover events involving tick-borne pathogens. Deep learning projections have indicated that the diversity of the H. longicornis virome is expected to increase in 81.9% of regions under the SSP8.5 scenario from 2019 to 2030. Extension of surveillance should be implemented to avert the spread of tick-borne diseases.

ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences.

BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract.

Association between Gut Microbiota Composition and Long-Term Vaccine Immunogenicity following Three Doses of CoronaVac.

BACKGROUND: Neutralizing antibody level wanes with time after COVID-19 vaccination. We aimed to study the relationship between baseline gut microbiota and immunogenicity after three doses of CoronaVac. METHODS: This was a prospective cohort study recruiting three-dose CoronaVac recipients from two centers in Hong Kong. Blood samples were collected at baseline and one year post-first dose for virus microneutralization (vMN) assays to determine neutralization titers. The primary outcome was high immune response (defined as with vMN titer ≥ 40). Shotgun DNA metagenomic sequencing of baseline fecal samples identified potential bacterial species and metabolic pathways using Linear Discriminant Analysis Effect Size (LEfSe) analysis. Univariate and multivariable logistic regression models were used to identify high response predictors. RESULTS: In total, 36 subjects were recruited (median age: 52.7 years [IQR: 47.9-56.4]; male: 14 [38.9%]), and 18 had low immune response at one year post-first dose vaccination. Eubacterium rectale (log10LDA score = 4.15, p = 0.001; relative abundance of 1.4% vs. 0, p = 0.002), Collinsella aerofaciens (log10LDA score = 3.31, p = 0.037; 0.39% vs. 0.18%, p = 0.038), and Streptococcus salivarius (log10LDA score = 2.79, p = 0.021; 0.05% vs. 0.02%, p = 0.022) were enriched in low responders. The aOR of high immune response with E. rectale, C. aerofaciens, and S. salivarius was 0.03 (95% CI: 9.56 × 10-4-0.32), 0.03 (95% CI: 4.47 × 10-4-0.59), and 10.19 (95% CI: 0.81-323.88), respectively. S. salivarius had a positive correlation with pathways enriched in high responders like incomplete reductive TCA cycle (log10LDA score = 2.23). C. aerofaciens similarly correlated with amino acid biosynthesis-related pathways. These pathways all showed anti-inflammation functions. CONCLUSION: E. rectale,C. aerofaciens, and S. salivarius correlated with poorer long-term immunogenicity following three doses of CoronaVac.

The Predictive Value of Gut Microbiota Composition for Sustained Immunogenicity following Two Doses of CoronaVac.

CoronaVac immunogenicity decreases with time, and we aimed to investigate whether gut microbiota associate with longer-term immunogenicity of CoronaVac. This was a prospective cohort study recruiting two-dose CoronaVac recipients from three centres in Hong Kong. We collected blood samples at baseline and day 180 after the first dose and used chemiluminescence immunoassay to test for neutralizing antibodies (NAbs) against the receptor-binding domain (RBD) of wild-type SARS-CoV-2 virus. We performed shotgun metagenomic sequencing performed on baseline stool samples. The primary outcome was the NAb seroconversion rate (seropositivity defined as NAb ≥ 15AU/mL) at day 180. Linear discriminant analysis [LDA] effect size analysis was used to identify putative bacterial species and metabolic pathways. A univariate logistic regression model was used to derive the odds ratio (OR) of seropositivity with bacterial species. Of 119 CoronaVac recipients (median age: 53.4 years [IQR: 47.8-61.3]; male: 39 [32.8%]), only 8 (6.7%) remained seropositive at 6 months after vaccination. Bacteroides uniformis (log10LDA score = 4.39) and Bacteroides eggerthii (log10LDA score = 3.89) were significantly enriched in seropositive than seronegative participants. Seropositivity was associated with B. eggerthii (OR: 5.73; 95% CI: 1.32-29.55; p = 0.022) and B. uniformis with borderline significance (OR: 3.27; 95% CI: 0.73-14.72; p = 0.110). Additionally, B. uniformis was positively correlated with most enriched metabolic pathways in seropositive vaccinees, including the superpathway of adenosine nucleotide de novo biosynthesis I (log10LDA score = 2.88) and II (log10LDA score = 2.91), as well as pathways related to vitamin B biosynthesis, all of which are known to promote immune functions. In conclusion, certain gut bacterial species (B. eggerthii and B. uniformis) and metabolic pathways were associated with longer-term CoronaVac immunogenicity.

Robust expansion of phylogeny for fast-growing genome sequence data.

Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ancestral sequences. It took about 21 seconds to insert 100 SARS-CoV-2 genomes into a 100k-taxa reference tree using 1.4 gigabytes. Benchmarking on four datasets, TIPars achieved the highest accuracy for phylogenies of moderately similar sequences. For highly similar and divergent scenarios, fully parsimony-based and likelihood-based phylogenetic placement methods performed the best respectively while TIPars was the second best. TIPars accomplished efficient and accurate expansion of phylogenies of both similar and divergent sequences, which would have broad biological applications beyond SARS-CoV-2. TIPars is accessible from https://tipars.hku.hk/ and source codes are available at https://github.com/id-bioinfo/TIPars.

Binding affinity between coronavirus spike protein and human ACE2 receptor.

Coronaviruses (CoVs) pose a major risk to global public health due to their ability to infect diverse animal species and potential for emergence in humans. The CoV spike protein mediates viral entry into the cell and plays a crucial role in determining the binding affinity to host cell receptors. With particular emphasis on α- and ß-coronaviruses that infect humans and domestic animals, current research on CoV receptor use suggests that the exploitation of the angiotensin-converting enzyme 2 (ACE2) receptor poses a significant threat for viral emergence with pandemic potential. This review summarizes the approaches used to study binding interactions between CoV spike proteins and the human ACE2 (hACE2) receptor. Solid-phase enzyme immunoassays and cell binding assays allow qualitative assessment of binding but lack quantitative evaluation of affinity. Surface plasmon resonance, Bio-layer interferometry, and Microscale Thermophoresis on the other hand, provide accurate affinity measurement through equilibrium dissociation constants (KD). In silico modeling predicts affinity through binding structure modeling, protein-protein docking simulations, and binding energy calculations but reveals inconsistent results due to the lack of a standardized approach. Machine learning and deep learning models utilize simulated and experimental protein-protein interaction data to elucidate the critical residues associated with CoV binding affinity to hACE2. Further optimization and standardization of existing approaches for studying binding affinity could aid pandemic preparedness. Specifically, prioritizing surveillance of CoVs that can bind to human receptors stands to mitigate the risk of zoonotic spillover.

Amino acid substitution L232F in non-structural protein 6 identified as a possible human-adaptive mutation in clade B MERS coronaviruses.

IMPORTANCE: Viral host adaptation plays an important role in inter-species transmission of coronaviruses and influenza viruses. Multiple human-adaptive mutations have been identified in influenza viruses but not so far in MERS-CoV that circulates widely in dromedary camels in the Arabian Peninsula leading to zoonotic transmission. Here, we analyzed clade B MERS-CoV sequences and identified an amino acid substitution L232F in nsp6 that repeatedly occurs in human MERS-CoV. Using a loss-of-function reverse genetics approach, we found the nsp6 L232F conferred increased viral replication competence in vitro, in cultures of the upper human respiratory tract ex vivo, and in lungs of mice infected in vivo. Our results showed that nsp6 L232F may be an adaptive mutation associated with zoonotic transmission of MERS-CoV. This study highlighted the capacity of MERS-CoV to adapt to transmission to humans and also the need for continued surveillance of MERS-CoV in camels.

Longitudinal monitoring reveals the emergence and spread of blaGES-5-harboring carbapenem-resistant Klebsiella quasipneumoniae in a Hong Kong hospital wastewater discharge line.

Testing hospital wastewater (HWW) is potentially an effective, long-term approach for monitoring trends in antimicrobial resistance (AMR) patterns in health care institutions. Over a year, we collected wastewater samples from the clinical and non-clinical sites of a tertiary hospital and from a downstream wastewater treatment plant (WWTP). We focused on the extent of carbapenem resistance among Enterobacteriaceae isolates given their clinical importance. Escherichia coli and Klebsiella spp. were the most frequently isolated Enterobacteriaceae species at all sampling sites. Additionally, a small number of isolates belonging to ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species), except K. pneumoniae, were detected. Of the 232 Klebsiella spp. isolates, 100 (43.1 %) were multi-drug resistant (MDR), with 46 being carbapenem-resistant. Most of these carbapenem-resistant isolates were K. quasipneumoniae (CRKQ) (n = 44). All CRKQ isolates were isolated from the wastewater of a clinical site that includes intensive care units, which also yielded significantly more multi-drug resistant isolates compared to all other sampling sites. Among the CRKQ isolates, blaGES-5 genes (n = 42) were the primary genetic determinant of carbapenem resistance. Notably, three different CRKQ isolates, collected within the same month in HWW and the influent and effluent flow of the WWTP, shared >99 % sequence similarity between their blaGES-5 genes and between their flanking regions and upstream integron-integrase region. The influent isolate was phylogenetically close to K. quasipnuemoniae isolates from wastewater collected in Japan. Its blaGES-5 gene and surrounding sequences were > 99 % identical to blaGES-24 genes found in the Japanese isolates. Our results suggest that testing samples from sites located closer to hospitals could support antibiotic stewardship programs compared to samples collected further downstream. Moreover, testing samples collected regularly from WWTPs may reflect the local and global spread of pathogens and their resistances.

Characterization of an Emergent Chicken H3N8 Influenza Virus in Southern China: a Potential Threat to Public Health.

Although influenza A viruses of several subtypes have occasionally infected humans, to date only those of the H1, H2, and H3 subtypes have led to pandemics and become established in humans. The detection of two human infections by avian H3N8 viruses in April and May of 2022 raised pandemic concerns. Recent studies have shown the H3N8 viruses were introduced into humans from poultry, although their genesis, prevalence, and transmissibility in mammals have not been fully elucidated. Findings generated from our systematic influenza surveillance showed that this H3N8 influenza virus was first detected in chickens in July 2021 and then disseminated and became established in chickens over wider regions of China. Phylogenetic analyses revealed that the H3 HA and N8 NA were derived from avian viruses prevalent in domestic ducks in the Guangxi-Guangdong region, while all internal genes were from enzootic poultry H9N2 viruses. The novel H3N8 viruses form independent lineages in the glycoprotein gene trees, but their internal genes are mixed with those of H9N2 viruses, indicating continuous gene exchange among these viruses. Experimental infection of ferrets with three chicken H3N8 viruses showed transmission through direct contact and inefficient transmission by airborne exposure. Examination of contemporary human sera detected only very limited antibody cross-reaction to these viruses. The continuing evolution of these viruses in poultry could pose an ongoing pandemic threat. IMPORTANCE A novel H3N8 virus with demonstrated zoonotic potential has emerged and disseminated in chickens in China. It was generated by reassortment between avian H3 and N8 virus(es) and long-term enzootic H9N2 viruses present in southern China. This H3N8 virus has maintained independent H3 and N8 gene lineages but continues to exchange internal genes with other H9N2 viruses to form novel variants. Our experimental studies showed that these H3N8 viruses were transmissible in ferrets, and serological data suggest that the human population lacks effective immunological protection against it. With its wide geographical distribution and continuing evolution in chickens, other spillovers to humans can be expected and might lead to more efficient transmission in humans.

Toward a Universal Unit for Quantification of Antibiotic Resistance Genes in Environmental Samples.

Surveillance of antibiotic resistance genes (ARGs) has been increasingly conducted in environmental sectors to complement the surveys in human and animal sectors under the "One-Health" framework. However, there are substantial challenges in comparing and synthesizing the results of multiple studies that employ different test methods and approaches in bioinformatic analysis. In this article, we consider the commonly used quantification units (ARG copy per cell, ARG copy per genome, ARG density, ARG copy per 16S rRNA gene, RPKM, coverage, PPM, etc.) for profiling ARGs and suggest a universal unit (ARG copy per cell) for reporting such biological measurements of samples and improving the comparability of different surveillance efforts.

Probable airborne transmission of Burkholderia pseudomallei causing an urban outbreak of melioidosis during typhoon season in Hong Kong, China.

Between January 2015 and October 2022, 38 patients with culture-confirmed melioidosis were identified in the Kowloon West (KW) Region, Hong Kong. Notably, 30 of them were clustered in the Sham Shui Po (SSP) district, which covers an estimated area of 2.5 km2. Between August and October 2022, 18 patients were identified in this district after heavy rainfall and typhoons. The sudden upsurge in cases prompted an environmental investigation, which involved collecting 20 air samples and 72 soil samples from residential areas near the patients. A viable isolate of Burkholderia pseudomallei was obtained from an air sample collected at a building site five days after a typhoon. B. pseudomallei DNA was also detected in 21 soil samples collected from the building site and adjacent gardening areas using full-length 16S rRNA gene sequencing, suggesting that B. psuedomallei is widely distributed in the soil environment surrounding the district. Core genome-multilocus sequence typing showed that the air sample isolate was phylogenetically clustered with the outbreak isolates in KW Region. Multispectral satellite imagery revealed a continuous reduction in vegetation region in SSP district by 162,255 m2 from 2016 to 2022, supporting the hypothesis of inhalation of aerosols from the contaminated soil as the transmission route of melioidosis during extreme weather events. This is because the bacteria in unvegetated soil are more easily spread by winds. In consistent with inhalational melioidosis, 24 (63.2%) patients had pneumonia. Clinicians should be aware of melioidosis during typhoon season and initiate appropriate investigation and treatment for patients with compatible symptoms.

Skin infectome of patients with a tick bite history.

Introduction: Ticks are the most important obligate blood-feeding vectors of human pathogens. With the advance of high-throughput sequencing, more and more bacterial community and virome in tick has been reported, which seems to pose a great threat to people. Methods: A total of 14 skin specimens collected from tick-bite patients with mild to severe symptoms were analyzed through meta-transcriptomic sequencings. Results: Four bacteria genera were both detected in the skins and ticks, including Pseudomonas, Acinetobacter, Corynebacterium and Propionibacterium, and three tick-associated viruses, Jingmen tick virus (JMTV), Bole tick virus 4 (BLTV4) and Deer tick mononegavirales-like virus (DTMV) were identified in the skin samples. Except of known pathogens such as pathogenic rickettsia, Coxiella burnetii and JMTV, we suggest Roseomonas cervicalis and BLTV4 as potential new agents amplified in the skins and then disseminated into the blood. As early as 1 day after a tick-bite, these pathogens can transmit to skins and at most four ones can co-infect in skins. Discussion: Advances in sequencing technologies have revealed that the diversity of tick microbiome and virome goes far beyond our previous understanding. This report not only identifies three new potential pathogens in humans but also shows that the skin barrier is vital in preventing horizontal transmissions of tick-associated bacteria or virus communities to the host. It is the first research on patients' skin infectome after a tick bite and demonstrates that more attention should be paid to the cutaneous response to prevent tick-borne illness.

New insights into the impact of microbiome on horizontal and vertical transmission of a tick-borne pathogen.

BACKGROUND: The impact of host skin microbiome on horizontal transmission of tick-borne pathogens , and of pathogen associated transstadial and transovarial changes in tick microbiome are largely unknown, but are important to control increasingly emerging tick-borne diseases worldwide. METHODS: Focusing on a rickettsiosis pathogen, Rickettsia raoultii, we used R. raoultii-positive and R. raoultii-negative Dermacentor spp. tick colonies to study the involvement of skin microbiota in cutaneous infection with rickettsiae in laboratory mice, and the function of the tick microbiome on maintenance of rickettsiae through all tick developmental stages (eggs, larvae, nymphs, adults) over two generations. RESULTS: We observed changes in the skin bacteria community, such as Chlamydia, not only associated with rickettsial colonization but also with tick feeding on skin. The diversity of skin microbiome differed between paired tick-bitten and un-bitten sites. For vertical transmission, significant differences in the tick microbiota between pathogenic rickettsia-positive and -negative tick chorts was observed across all developmental stages at least over two generations, which appeared to be a common pattern not only for R. raoultii but also for another pathogenic species, Candidatus Rickettsia tarasevichiae. More importantly, bacterial differences were complemented by functional shifts primed for genetic information processing during blood feeding. Specifically, the differences in tick microbiome gene repertoire between pathogenic Rickettsia-positive and -negative progenies were enriched in pathways associated with metabolism and hormone signals during vertical transmission. CONCLUSIONS: We demonstrate that host skin microbiome might be a new factor determining the transmission of rickettsial pathogens through ticks. While pathogenic rickettsiae infect vertebrate hosts during blood-feeding by the tick, they may also manipulate the maturation of the tick through changing the functional potential of its microbiota over the tick's life stages. The findings here might spur the development of new-generation control methods for ticks and tick-borne pathogens. Video Abstract.