Temporal transcriptome change of Oncomelania hupensis revealed by Schistosoma japonicum invasion

Weighted gene co-expression network analysis reveals immune evasion related genes in Echinococcus granulosus sensu stricto

Cystic echinococcosis (CE) is a zoonotic disease caused by the tapeworm Echinococcus granulosus sensu lato (s.l). In the intermediate host, this disease is characterized by the growth of cysts in viscera such as liver and lungs, inside of which the parasite develops to the next infective stage known as protoscoleces. There are records that the infected viscera affect the development and morphology of E. granulosus s.l. protoscolex in hosts such as buffalo or humans. However, the molecular mechanisms that drive these differences remains unknown. Weighted gene co-expression network analysis (WGCNA) using a set of RNAseq data obtained from E. granulosus sensu stricto (s.s.) protoscoleces found in liver and lung cysts reveals 34 modules in protoscoleces of liver origin, of which 12 have differential co-expression from protoscoleces of lung origin. Three of these twelve modules contain hub genes related to immune evasion: tegument antigen, tegumental protein, ubiquitin hydrolase isozyme L3, COP9 signalosome complex subunit 3, tetraspanin CD9 antigen, and the methyl-CpG-binding protein Mbd2. Also, two of the twelve modules contain only hypothetical proteins with unknown orthology, which means that there are a group of unknown function proteins co-expressed inside the protoscolex of liver CE cyst origin. This is the first evidence of gene expression differences in protoscoleces from CE cysts found in different viscera, with co-expression networks that are exclusive to protoscoleces from liver CE cyst samples. This should be considered in the control strategies of CE, as intermediate hosts can harbor CE cysts in liver, lungs, or both organs simultaneously.

Chromosome-scale genome of the human blood fluke Schistosoma mekongi and its implications for public health

BACKGROUND

Schistosoma mekongi is a human blood fluke causing schistosomiasis that threatens approximately 1.5 million humans in the world. Nonetheless, the limited available S. mekongi genomic resources have hindered understanding of its biology and parasite-host interactions for disease management and pathogen control. The aim of our study was to integrate multiple technologies to construct a high-quality chromosome-level assembly of the S. mekongi genome.

METHODS

The reference genome for S. mekongi was generated through integrating Illumina, PacBio sequencing, 10 × Genomics linked-read sequencing, and high-throughput chromosome conformation capture (Hi-C) methods. In this study, we conducted de novo assembly, alignment, and gene prediction to assemble and annotate the genome. Comparative genomics allowed us to compare genomes across different species, shedding light on conserved regions and evolutionary relationships. Additionally, our transcriptomic analysis focused on genes associated with parasite-snail interactions in S. mekongi infection. We employed gene ontology (GO) enrichment analysis for functional annotation of these genes.

RESULTS

In the present study, the S. mekongi genome was both assembled into 8 pseudochromosomes with a length of 404 Mb, with contig N50 and scaffold N50 lengths of 1168 kb and 46,759 kb, respectively. We detected that 43% of the genome consists of repeat sequences and predicted 9103 protein-coding genes. We also focused on proteases, particularly leishmanolysin-like metalloproteases (M8), which are crucial in the invasion of hosts by 12 flatworm species. Through phylogenetic analysis, it was discovered that the M8 gene exhibits lineage-specific amplification among the genus Schistosoma. Lineage-specific expansion of M8 was observed in blood flukes. Additionally, the results of the RNA-seq revealed that a mass of genes related to metabolic and biosynthetic processes were up-regulated, which might be beneficial for cercaria production.

CONCLUSIONS

This study delivers a high-quality, chromosome-scale reference genome of S. mekongi, enhancing our understanding of the divergence and evolution of Schistosoma. The molecular research conducted here also plays a pivotal role in drug discovery and vaccine development. Furthermore, our work greatly advances the understanding of host-parasite interactions, providing crucial insights for schistosomiasis intervention strategies.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

BACKGROUND

Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence.

METHODS

In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data.

RESULTS

The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen's kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (an indicator of surface water presence) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways.

CONCLUSION

Our results suggest that in low-transmission environments, leveraging open-source environmental data can yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Open-source environmental data as an alternative to snail surveys to assess schistosomiasis risk in areas approaching elimination

Background: Although the presence of intermediate snails is a necessary condition for local schistosomiasis transmission to occur, using them as surveillance targets in areas approaching elimination is challenging because the patchy and dynamic quality of snail host habitats makes collecting and testing snails labor-intensive. Meanwhile, geospatial analyses that rely on remotely sensed data are becoming popular tools for identifying environmental conditions that contribute to pathogen emergence and persistence. Methods: In this study, we assessed whether open-source environmental data can be used to predict the presence of human Schistosoma japonicum infections among households with a similar or improved degree of accuracy compared to prediction models developed using data from comprehensive snail surveys. To do this, we used infection data collected from rural communities in Southwestern China in 2016 to develop and compare the predictive performance of two Random Forest machine learning models: one built using snail survey data, and one using open-source environmental data. Results: The environmental data models outperformed the snail data models in predicting household S. japonicum infection with an estimated accuracy and Cohen’s kappa value of 0.89 and 0.49, respectively, in the environmental model, compared to an accuracy and kappa of 0.86 and 0.37 for the snail model. The Normalized Difference in Water Index (NDWI) within half to one kilometer of the home and the distance from the home to the nearest road were among the top performing predictors in our final model. Homes were more likely to have infected residents if they were further from roads, or nearer to waterways. Conclusion: Our results suggest that in low-transmission environments, investing in training geographic information systems professionals to leverage open-source environmental data could yield more accurate identification of pockets of human infection than using snail surveys. Furthermore, the variable importance measures from our models point to aspects of the local environment that may indicate increased risk of schistosomiasis. For example, households were more likely to have infected residents if they were further from roads or were surrounded by more surface water, highlighting areas to target in future surveillance and control efforts.

Transcriptomic profiling of immune-associated molecules in the coelomocytes of lugworm Arenicola marina (Linnaeus, 1758)

Organization and functioning of immune system remain unevenly studied in different taxa of lophotrochozoan animals. We analyzed transcriptomic data on coelomocytes of the lugworm Arenicola marina (Linnaeus, 1758; Annelida, Polychaeta) to gain insights into the molecular mechanisms involved in polychaete immunity. Coelomocytes are specialized motile cells populating coelomic fluid of annelids, responsible for cellular defense reactions and providing humoral immune factors. The transcriptome was enriched with immune-related transcripts by challenging the cells in vitro with lipopolysaccharides of Escherichia coli and Zymosan from Saccharomyces cerevisiae. Our analysis revealed a multifaceted and complex internal defense system of the lugworm. A. marina possesses orthologs of proto-complement-like factors: six thioester-containing proteins, a complement-like receptor, and a MASP-related serine protease (MReM2). A. marina coelomocytes employ pattern-recognition receptors to detect pathogens and regulate immune responses. Among them, there are 18 Toll-like receptors and various putative lectin-like proteins with evolutionary conserved and taxa-specific domains. C-type lectins and a novel family of Gal-binding and CUB domains containing receptors were the most abundant in the transcriptome. The array of pore-forming proteins in the coelomocytes was surprisingly reduced compared to that of other invertebrate species. We characterized a set of conserved proteins metabolizing reactive oxygen species and nitric oxide and expanded the arsenal of potential antimicrobial peptides. Phenoloxidase activity in immune cells of lugworm is mediated only by laccase enzyme. The described repertoire of immune-associated molecules provides valuable candidates for further functional and comparative research on the immunity of annelids.

Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber, Apostichopus japonicus

The papilla number is one of the most economically important traits of sea cucumber in the China marketing trade. However, the genetic basis for papilla number diversity in holothurians is still scarce. In the present study, we conducted genome-wide association studies (GWAS) for the trait papilla number of sea cucumbers utilizing a set of 400,186 high-quality SNPs derived from 200 sea cucumbers. Two significant trait-associated SNPs that passed Bonferroni correction (P < 1.25E-7) were located in the intergenic region near PATS1 and the genic region of EIF4G, which were reported to play a pivotal role in cell growth and proliferation. The fine-mapping regions around the top two lead SNPs provided precise causative loci/genes related to papilla formation and cellular activity, including PPP2R3C, GBP1, and BCAS3. Potential SNPs with P < 1E-4 were acquired for the following GO and KEGG enrichment analysis. Moreover, the two lead SNPs were verified in another population of sea cucumber, and the expressive detection of three potential candidate genes PATS1, PPP2R3C, and EIF4G that near or cover the two lead SNPs was conducted in papilla tissue of TG (Top papilla number group) and BG (Bottom papilla number group) by qRT-PCR. We found the significantly higher expression profile of PATS1 (3.34-fold), PPP2R3C (4.90-fold), and EIF4G (4.23-fold) in TG, implying their potential function in papilla polymorphism. The present results provide valuable information to decipher the phenotype differences of the papilla trait and will provide a scientific basis for selective breeding in sea cucumbers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-022-00139-w.

Integrated bioinformatics data analysis reveals a risk signature and PKD1 induced progression in endometrial cancer patients with postmenopausal status

Background: Endometrial cancer (EC) is one of the most common type of female genital malignancies. The purpose of the present study was to reveal the underlying oncogene and mechanism that played a pivotal role in postmenopausal EC patients.

Methods: Weighted gene co-expression network analysis (WGCNA) was conducted using the microarray dataset and clinical data of EC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify significant gene modules and hub genes associated with postmenopausal status in EC patients. LASSO regression was conducted to build and validate the risk model. Finally, expression of hub gene was validated in pre- and post-menopausal EC patients in our center.

Results: 1240 common genes were used to construct the WGCNA model. According to the WGCNA results, we identified a brown module with 471 genes which was significantly associated with postmenopausal status in EC patients. Furthermore, we constructed an 11-gene risk signature to predict the overall survival of EC patients. The Kaplan–Meier curve and area under the ROC curve (AUC) of this model showed high accuracy in prediction. We also validate the risk model in patients in our center and it also has a high accuracy. Among the 11 genes, PKD1 was recognized as a potential biomarker in the progression of EC patients with postmenopausal status.

Conclusion: Taken together, we uncovered a common PKD1-mediated mechanism underlying postmenopausal EC patients’ progression by integrated analyses. This finding may improve targeted therapy for EC patients.

Transcriptome analysis of Aedes albopictus midguts infected by dengue virus identifies a gene network module highly associated with temperature

BACKGROUND

Dengue is prevalent worldwide and is transmitted by Aedes mosquitoes. Temperature is a strong driver of dengue transmission. However, little is known about the underlying mechanisms.

METHODS

Aedes albopictus mosquitoes exposed or not exposed to dengue virus serotype 2 (DENV-2) were reared at 23 °C, 28 °C and 32 °C, and midguts and residual tissues were evaluated at 7 days after infection. RNA sequencing of midgut pools from the control group, midgut breakthrough group and midgut nonbreakthrough group at different temperatures was performed. The transcriptomic profiles were analyzed using the R package, followed by weighted gene correlation network analysis (WGCNA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify the important molecular mechanisms regulated by temperature.

RESULTS

The midgut infection rate and midgut breakthrough rate at 28 °C and 32 °C were significantly higher than those at 23 °C, which indicates that high temperature facilitates DENV-2 breakthrough in the Ae. albopictus midgut. Transcriptome sequencing was performed to investigate the antiviral mechanism in the midgut. The midgut gene expression datasets clustered with respect to temperature, blood-feeding and midgut breakthrough. Over 1500 differentially expressed genes were identified by pairwise comparisons of midguts at different temperatures. To assess key molecules regulated by temperature, we used WGCNA, which identified 28 modules of coexpressed genes; the ME3 module correlated with temperature. KEGG analysis indicated that RNA degradation, Toll and immunodeficiency factor signaling and other pathways are regulated by temperature.

CONCLUSIONS

Temperature affects the infection and breakthrough of Ae. albopictus midguts invaded by DENV-2, and Ae. albopictus midgut transcriptomes change with temperature. The candidate genes and key pathways regulated by temperature provide targets for the prevention and control of dengue.

Reappearance of Risk of Schistosomiasis Transmission and the Response After 27 Years of Interrupted Transmission - Guangdong Province, China, 2019

What is already known about this topic?

No live specimens of the snail Oncomelania hupensis (O. hupensis) and indigenous infected cases of schistosomiasis japonicum have been found in Guangdong Province since 1993, but live O. hupensis was found again in 2019. This study conducted O. hupensis identification and elimination.

What is added by this report?

In 2019, live O. hupensis specimens were detected by routine surveillance in areas in Qujiang of Shaoguan City and Yingde of Qingyuan City, and an emergency response was launched immediately.

What are the implications for public health practice?

The suspected habitat of O. hupensis in originally endemic areas of schistosomiasis in Guangdong is still complicated, so it is necessary to record suspected habitats comprehensively and carry out scientific routine surveillance for O. hupensis.

Genome-Wide Association Study Reveals PC4 as the Candidate Gene for Thermal Tolerance in Bay Scallop (Argopecten irradians irradians)

The increasing sea temperature caused by global warming has resulted in severe mortalities in maricultural scallops. Therefore, improving thermal tolerance has become an active research area in the scallop farming industry. Bay scallop (Argopecten irradians irradians) was introduced into China in 1982 and has developed into a vast aquaculture industry in northern China. To date, genetic studies on thermal tolerance in bay scallops are limited, and no systematic screening of thermal tolerance-related loci or genes has been conducted in this species. In the present study, we conducted a genome-wide association study (GWAS) for thermal tolerance using the Arrhenius break temperature (ABT) indicators of 435 bay scallops and 38,011 single nucleotide polymorphism (SNP) markers. The GWAS identified 1,906 significant thermal tolerance-associated SNPs located in 16 chromosomes of bay scallop. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that 638 genes were enriched in 42 GO terms, while 549 annotated genes were enriched in aggregation pathways. Additionally, the SNP (15-5091-20379557-1) with the lowest P value was located in the transcriptional coactivator p15 (PC4) gene, which is involved in regulating DNA damage repair and stabilizing genome functions. Further analysis in another population identified two new thermal tolerance-associated SNPs in the first coding sequence of PC4 in bay scallops (AiPC4). Moreover, AiPC4 expression levels were significantly correlated (r = 0.675–0.962; P < 0.05) with the ABT values of the examined bay scallops. Our data suggest that AiPC4 might be a positive regulator of thermal tolerance and a potential candidate gene for molecular breeding in bay scallop aiming at thermal tolerance improvement.

Toll-like signaling pathway in the transcriptome of Littorina littorea

The transcriptome of the caenogastropod mollusk Littorina littorea was scanned for the presence of sequences encoding Toll-like receptors (TLRs) and corresponding proteins involved in downstream TLR signaling pathway. In the transcriptomic snapshots of hemocytes and kidney tissues, 45 complete TLRs encoded by 35 genes were identified. Out of the 59 non-TLR molecules involved in a canonical TLR signaling pathway, 35 genes were classified as homologous and could be placed within the TLR-mediated MyD88-and MAPK-dependent circuitries. No reference vertebrate adapters TIRAP, TRIF and TRAM were identified in the transcriptome. The results of RNA-seq experiments with an immune challenge (rediae of the digenean Himasthla elongata) indicate that four TLRs (LlTLR1, 3, 5 and 8) and a set of upregulated genes involved in signal transduction (LlMyd88, LlTNFα, LlCASP8, LlFADD, LlNFKBIA (IkBα), LlIRAK1, LlSTAT1, LlMAPK14 (P38), LlMAP2K1 (MEK1/2), LlIRF3 and LlIRF5) may participate in the anti-digenean immune response of L. littorea.