Chuang, Hsiu-Chun, Ruidong, Li, Li, Li, Kai-Hui, Sun Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3 Journal Article In: BMC Genomics, 2024. @article{noKey,
title = {Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3},
author = {Chuang, Hsiu-Chun, Ruidong, Li, Li, Li, Kai-Hui, Sun},
url = {https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-024-11036-0},
doi = {https://doi.org/10.1186/s12864-024-11036-0},
year = {2024},
date = {2024-11-20},
journal = {BMC Genomics},
abstract = {We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow that integrates best practices and an optimized protocol to enhance efficiency, scalability, and method reproducibility. This workflow consistently produces high-quality data with high cell capture efficiency and gene detection sensitivity. In a rigorous comparison with the 10X platform using human primary CD4 + T-cells, HT Smart-seq3 demonstrated higher cell capture efficiency, greater gene detection sensitivity, and lower dropout rates. Additionally, when sufficiently scaled, HT Smart-seq3 achieved a comparable resolution of cellular heterogeneity to 10X. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified a greater number of productive alpha and beta chain pairs without the need for additional primer design to amplify full-length V(D)J segments, enabling more comprehensive TCR profiling across a broader range of species. Taken together, HT Smart-seq3 overcomes key technical challenges, offering distinct advantages that position it as a promising solution for the characterization of single-cell transcriptomes and immune repertoires, particularly well-suited for low-input, low-RNA content samples.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
We developed an automated high-throughput Smart-seq3 (HT Smart-seq3) workflow that integrates best practices and an optimized protocol to enhance efficiency, scalability, and method reproducibility. This workflow consistently produces high-quality data with high cell capture efficiency and gene detection sensitivity. In a rigorous comparison with the 10X platform using human primary CD4 + T-cells, HT Smart-seq3 demonstrated higher cell capture efficiency, greater gene detection sensitivity, and lower dropout rates. Additionally, when sufficiently scaled, HT Smart-seq3 achieved a comparable resolution of cellular heterogeneity to 10X. Notably, through T-cell receptor (TCR) reconstruction, HT Smart-seq3 identified a greater number of productive alpha and beta chain pairs without the need for additional primer design to amplify full-length V(D)J segments, enabling more comprehensive TCR profiling across a broader range of species. Taken together, HT Smart-seq3 overcomes key technical challenges, offering distinct advantages that position it as a promising solution for the characterization of single-cell transcriptomes and immune repertoires, particularly well-suited for low-input, low-RNA content samples. |
Wang, Hongliang, Skim exome capture genotyping in wheat Journal Article In: The Plant Genome, 2023. @article{noKey,
title = {Skim exome capture genotyping in wheat},
author = {Wang, Hongliang,},
url = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20381},
doi = {https://doi.org/10.1002/tpg2.20381},
year = {2023},
date = {2023-08-20},
journal = {The Plant Genome},
abstract = {Next-generation sequencing (NGS) technology advancements continue to reduce the cost of high-throughput genome-wide genotyping for breeding and genetics research. Skim sequencing, which surveys the entire genome at low coverage, has become feasible for quantitative trait locus (QTL) mapping and genomic selection in various crops. However, the genome complexity of allopolyploid crops such as wheat (Triticum aestivum L.) still poses a significant challenge for genome-wide genotyping. Targeted sequencing of the protein-coding regions (i.e., exome) reduces sequencing costs compared to whole genome re-sequencing and can be used for marker discovery and genotyping. We developed a method called skim exome capture (SEC) that combines the strengths of these existing technologies and produces targeted genotyping data while decreasing the cost on a per-sample basis compared to traditional exome capture. Specifically, we fragmented genomic DNA using a tagmentation approach, then enriched those fragments for the low-copy genic portion of the genome using commercial wheat exome baits and multiplexed the sequencing at different levels to achieve desired coverage. We demonstrated that for a library of 48 samples, ∼7–8× target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1056 samples per library, we achieved an average coverage of 0.76× and 0.32×, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database that we developed, we identified hundreds of thousands of high-quality genic variants across the genome. The SEC method can be used for high-resolution QTL mapping, genome-wide association studies, genomic selection, and other downstream applications.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Next-generation sequencing (NGS) technology advancements continue to reduce the cost of high-throughput genome-wide genotyping for breeding and genetics research. Skim sequencing, which surveys the entire genome at low coverage, has become feasible for quantitative trait locus (QTL) mapping and genomic selection in various crops. However, the genome complexity of allopolyploid crops such as wheat (Triticum aestivum L.) still poses a significant challenge for genome-wide genotyping. Targeted sequencing of the protein-coding regions (i.e., exome) reduces sequencing costs compared to whole genome re-sequencing and can be used for marker discovery and genotyping. We developed a method called skim exome capture (SEC) that combines the strengths of these existing technologies and produces targeted genotyping data while decreasing the cost on a per-sample basis compared to traditional exome capture. Specifically, we fragmented genomic DNA using a tagmentation approach, then enriched those fragments for the low-copy genic portion of the genome using commercial wheat exome baits and multiplexed the sequencing at different levels to achieve desired coverage. We demonstrated that for a library of 48 samples, ∼7–8× target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1056 samples per library, we achieved an average coverage of 0.76× and 0.32×, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database that we developed, we identified hundreds of thousands of high-quality genic variants across the genome. The SEC method can be used for high-resolution QTL mapping, genome-wide association studies, genomic selection, and other downstream applications. |
Yajima, Daii Core species and interactions prominent in fish-associated microbiome dynamics Journal Article In: Microbiome, 2023. @article{noKey,
title = {Core species and interactions prominent in fish-associated microbiome dynamics},
author = {Yajima, Daii},
url = {https://link.springer.com/article/10.1186/s40168-023-01498-x},
doi = {https://doi.org/10.1186/s40168-023-01498-x},
year = {2023},
date = {2023-03-19},
journal = {Microbiome},
abstract = {Background
In aquatic ecosystems, the health and performance of fish depend greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fish’s performance out of thousands of candidate species remains a major challenge.
Methods
We examined whether time-series analyses of microbial population dynamics could illuminate core components and structure of fish-associated microbiomes in the background (environmental) water. By targeting eel-aquaculture-tank microbiomes as model systems, we reconstructed the population dynamics of the 9605 bacterial and 303 archaeal species/strains across 128 days.
Results
Due to the remarkable increase/decrease of constituent microbial population densities, the taxonomic compositions of the microbiome changed drastically through time. We then found that some specific microbial taxa showed a positive relationship with eels’ activity levels even after excluding confounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin-B12-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels’ activity levels across the replicate time series of the five aquaculture tanks analyzed. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium and some other closely-associated bacteria formed “core microbiomes” with potentially positive impacts on eels.
Conclusions
Overall, these results suggest that the integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Background
In aquatic ecosystems, the health and performance of fish depend greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fish’s performance out of thousands of candidate species remains a major challenge.
Methods
We examined whether time-series analyses of microbial population dynamics could illuminate core components and structure of fish-associated microbiomes in the background (environmental) water. By targeting eel-aquaculture-tank microbiomes as model systems, we reconstructed the population dynamics of the 9605 bacterial and 303 archaeal species/strains across 128 days.
Results
Due to the remarkable increase/decrease of constituent microbial population densities, the taxonomic compositions of the microbiome changed drastically through time. We then found that some specific microbial taxa showed a positive relationship with eels’ activity levels even after excluding confounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin-B12-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels’ activity levels across the replicate time series of the five aquaculture tanks analyzed. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium and some other closely-associated bacteria formed “core microbiomes” with potentially positive impacts on eels.
Conclusions
Overall, these results suggest that the integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes. |
Huang, Yiming High-throughput microbial culturomics using automation and machine learning Journal Article In: Nature biotechnology, 2023. @article{noKey,
title = {High-throughput microbial culturomics using automation and machine learning},
author = {Huang, Yiming},
url = {https://www.nature.com/articles/s41587-023-01674-2},
doi = {https://doi.org/10.1038/s41587-023-01674-2},
year = {2023},
date = {2023-02-19},
journal = {Nature biotechnology},
abstract = {Pure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype–genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Pure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype–genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies. |
Albors, Aida Rodrigo, et al. An ependymal cell census identifies heterogeneous and ongoing cell maturation in the adult mouse spinal cord that changes dynamically on injury Journal Article In: Developmental Cell, 2023. @article{noKey,
title = {An ependymal cell census identifies heterogeneous and ongoing cell maturation in the adult mouse spinal cord that changes dynamically on injury},
author = {Albors, Aida Rodrigo, et al.},
url = {https://pubmed.ncbi.nlm.nih.gov/36706756/},
doi = {https://doi.org/10.1016/j.devcel.2023.01.003},
year = {2023},
date = {2023-01-18},
journal = {Developmental Cell},
abstract = {The adult spinal cord stem cell potential resides within the ependymal cell population and declines with age. Ependymal cells are, however, heterogeneous, and the biological diversity this represents and how it changes with age remain unknown. Here, we present a single-cell transcriptomic census of spinal cord ependymal cells from adult and aged mice, identifying not only all known ependymal cell subtypes but also immature as well as mature cell states. By comparing transcriptomes of spinal cord and brain ependymal cells, which lack stem cell abilities, we identify immature cells as potential spinal cord stem cells. Following spinal cord injury, these cells re-enter the cell cycle, which is accompanied by a short-lived reversal of ependymal cell maturation. We further analyze ependymal cells in the human spinal cord and identify widespread cell maturation and altered cell identities. This in-depth characterization of spinal cord ependymal cells provides insight into their biology and informs strategies for spinal cord repair.},
keywords = {Tempest®},
pubstate = {published},
tppubtype = {article}
}
The adult spinal cord stem cell potential resides within the ependymal cell population and declines with age. Ependymal cells are, however, heterogeneous, and the biological diversity this represents and how it changes with age remain unknown. Here, we present a single-cell transcriptomic census of spinal cord ependymal cells from adult and aged mice, identifying not only all known ependymal cell subtypes but also immature as well as mature cell states. By comparing transcriptomes of spinal cord and brain ependymal cells, which lack stem cell abilities, we identify immature cells as potential spinal cord stem cells. Following spinal cord injury, these cells re-enter the cell cycle, which is accompanied by a short-lived reversal of ependymal cell maturation. We further analyze ependymal cells in the human spinal cord and identify widespread cell maturation and altered cell identities. This in-depth characterization of spinal cord ependymal cells provides insight into their biology and informs strategies for spinal cord repair. |
Wang, Haichuan, Campbell, Benjamin Development of Molecular Inversion Probes for Soybean Progeny Genomic Selection Genotyping Journal Article In: The Plant Genome, 2022. @article{noKey,
title = {Development of Molecular Inversion Probes for Soybean Progeny Genomic Selection Genotyping},
author = {Wang, Haichuan, Campbell, Benjamin},
url = {https://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20270},
doi = {https://doi.org/10.1002/tpg2.20270},
year = {2022},
date = {2022-11-20},
journal = {The Plant Genome},
abstract = {Increasing rate of genetic gain for key agronomic traits through genomic selection requires the development of new molecular methods to run genome-wide single nucleotide polymorphisms (SNPs). The main limitation of current methods is the cost is too high to screen breeding populations. Molecular inversion probes (MIPs) is a targeted genotyping-by-sequencing method that could be used for soybeans that is both cost effective, high-throughput, and provides high data quality to screen breeder’s germplasm for genomic selection. A 1K MIP SNP set was developed for soybean with uniformly distributed markers across the genome. The SNPs were selected to maximize the number of informative markers in germplasm being tested in soybean breeding programs located in the North Central and Mid-South regions of the United States. The 1K SNP MIP set was tested on diverse germplasm and a recombinant inbred line population. Targeted sequencing with MIPs obtained an 85% enrichment for the targeted SNPs. MIP’s genotyping accuracy was 93% overall while homozoygous call accuracy was 98% with less than 10% missing data. The accuracy of MIPs combined with its low per sample cost makes it a powerful tool to enable genomic selection within soybean breeding programs.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Increasing rate of genetic gain for key agronomic traits through genomic selection requires the development of new molecular methods to run genome-wide single nucleotide polymorphisms (SNPs). The main limitation of current methods is the cost is too high to screen breeding populations. Molecular inversion probes (MIPs) is a targeted genotyping-by-sequencing method that could be used for soybeans that is both cost effective, high-throughput, and provides high data quality to screen breeder’s germplasm for genomic selection. A 1K MIP SNP set was developed for soybean with uniformly distributed markers across the genome. The SNPs were selected to maximize the number of informative markers in germplasm being tested in soybean breeding programs located in the North Central and Mid-South regions of the United States. The 1K SNP MIP set was tested on diverse germplasm and a recombinant inbred line population. Targeted sequencing with MIPs obtained an 85% enrichment for the targeted SNPs. MIP’s genotyping accuracy was 93% overall while homozoygous call accuracy was 98% with less than 10% missing data. The accuracy of MIPs combined with its low per sample cost makes it a powerful tool to enable genomic selection within soybean breeding programs. |
Belote, Rachel L., Le, Daniel Human melanocyte development and melanoma dedifferentiation at single-cell resolution Journal Article In: Nature Cell Biology, 2021. @article{noKey,
title = {Human melanocyte development and melanoma dedifferentiation at single-cell resolution},
author = {Belote, Rachel L., Le, Daniel},
url = {https://www.nature.com/articles/s41556-021-00740-8},
doi = {https://doi.org/10.1038/s41556-021-00740-8},
year = {2021},
date = {2021-09-01},
journal = {Nature Cell Biology},
abstract = {In humans, epidermal melanocytes are responsible for skin pigmentation, defence against ultraviolet radiation and the deadliest common skin cancer, melanoma. Although there is substantial overlap in melanocyte development pathways between different model organisms, species-dependent differences are frequent and the conservation of these processes in human skin remains unresolved. Here, we used a single-cell enrichment and RNA-sequencing pipeline to study human epidermal melanocytes directly from the skin, capturing transcriptomes across different anatomical sites, developmental age, sexes and multiple skin tones. We uncovered subpopulations of melanocytes that exhibit anatomical site-specific enrichment that occurs during gestation and persists through adulthood. The transcriptional signature of the volar-enriched subpopulation is retained in acral melanomas. Furthermore, we identified human melanocyte differentiation transcriptional programs that are distinct from gene signatures generated from model systems. Finally, we used these programs to define patterns of dedifferentiation that are predictive of melanoma prognosis and response to immune checkpoint inhibitor therapy.},
keywords = {Tempest®},
pubstate = {published},
tppubtype = {article}
}
In humans, epidermal melanocytes are responsible for skin pigmentation, defence against ultraviolet radiation and the deadliest common skin cancer, melanoma. Although there is substantial overlap in melanocyte development pathways between different model organisms, species-dependent differences are frequent and the conservation of these processes in human skin remains unresolved. Here, we used a single-cell enrichment and RNA-sequencing pipeline to study human epidermal melanocytes directly from the skin, capturing transcriptomes across different anatomical sites, developmental age, sexes and multiple skin tones. We uncovered subpopulations of melanocytes that exhibit anatomical site-specific enrichment that occurs during gestation and persists through adulthood. The transcriptional signature of the volar-enriched subpopulation is retained in acral melanomas. Furthermore, we identified human melanocyte differentiation transcriptional programs that are distinct from gene signatures generated from model systems. Finally, we used these programs to define patterns of dedifferentiation that are predictive of melanoma prognosis and response to immune checkpoint inhibitor therapy. |
Topcu, Yasin, Sapkota, Manoj Identification of blossom-end rot loci using joint QTL-seq and linkage-based QTL mapping in tomato Journal Article In: Theoretical and Applied Genetics, 2021. @article{noKey,
title = {Identification of blossom-end rot loci using joint QTL-seq and linkage-based QTL mapping in tomato},
author = {Topcu, Yasin, Sapkota, Manoj},
url = {https://link.springer.com/article/10.1007/s00122-021-03869-0},
doi = {https://doi.org/10.1007/s00122-021-03869-0},
year = {2021},
date = {2021-06-13},
journal = {Theoretical and Applied Genetics},
abstract = {Blossom-end rot (BER) is a devastating physiological disorder that affects tomato and other vegetables, resulting in significant crop losses. To date, most studies on BER have focused on the environmental factors that affect calcium translocation to the fruit; however, the genetic basis of this disorder remains unknown. To investigate the genetic basis of BER, two F2 and F3:4 populations along with a BC1 population that segregated for BER occurrence were evaluated in the greenhouse. Using the QTL-seq approach, quantitative trait loci (QTL) associated with BER Incidence were identified at the bottom of chromosome (ch) 3 and ch11. Additionally, linkage-based QTL mapping detected another QTL, BER3.1, on ch3 and BER4.1 on ch4. To fine map the QTLs identified by QTL-seq, recombinant screening was performed. BER3.2, the major BER QTL on ch3, was narrowed down from 5.68 to 1.58 Mbp with a 1.5-LOD support interval (SI) corresponding to 209 candidate genes. BER3.2 colocalizes with the fruit weight gene FW3.2/SlKLUH, an ortholog of cytochrome P450 KLUH in Arabidopsis. Further, BER11.1, the major BER QTL on ch11, was narrowed down from 3.99 to 1.13 Mbp with a 1.5-LOD SI interval comprising of 141 candidate genes. Taken together, our results identified and fine mapped the first loci for BER resistance in tomato that will facilitate marker-assistant breeding not only in tomato but also in many other vegetables suffering for BER.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Blossom-end rot (BER) is a devastating physiological disorder that affects tomato and other vegetables, resulting in significant crop losses. To date, most studies on BER have focused on the environmental factors that affect calcium translocation to the fruit; however, the genetic basis of this disorder remains unknown. To investigate the genetic basis of BER, two F2 and F3:4 populations along with a BC1 population that segregated for BER occurrence were evaluated in the greenhouse. Using the QTL-seq approach, quantitative trait loci (QTL) associated with BER Incidence were identified at the bottom of chromosome (ch) 3 and ch11. Additionally, linkage-based QTL mapping detected another QTL, BER3.1, on ch3 and BER4.1 on ch4. To fine map the QTLs identified by QTL-seq, recombinant screening was performed. BER3.2, the major BER QTL on ch3, was narrowed down from 5.68 to 1.58 Mbp with a 1.5-LOD support interval (SI) corresponding to 209 candidate genes. BER3.2 colocalizes with the fruit weight gene FW3.2/SlKLUH, an ortholog of cytochrome P450 KLUH in Arabidopsis. Further, BER11.1, the major BER QTL on ch11, was narrowed down from 3.99 to 1.13 Mbp with a 1.5-LOD SI interval comprising of 141 candidate genes. Taken together, our results identified and fine mapped the first loci for BER resistance in tomato that will facilitate marker-assistant breeding not only in tomato but also in many other vegetables suffering for BER. |
Mamanova, Lira, Miao et al, Zhichao High-throughput full-length single-cell RNA-seq automation Journal Article In: Nature Protocols, 2021. @article{noKey,
title = {High-throughput full-length single-cell RNA-seq automation},
author = {Mamanova, Lira, Miao et al, Zhichao},
url = {https://www.nature.com/articles/s41596-021-00523-3},
doi = {https://doi.org/10.1038/s41596-021-00523-3},
year = {2021},
date = {2021-05-13},
journal = {Nature Protocols},
abstract = {Existing protocols for full-length single-cell RNA sequencing produce libraries of high complexity (thousands of distinct genes) with outstanding sensitivity and specificity of transcript quantification. These full-length libraries have the advantage of allowing probing of transcript isoforms, are informative regarding single-nucleotide polymorphisms and allow assembly of the VDJ region of the T- and B-cell-receptor sequences. Since full-length protocols are mostly plate-based at present, they are also suited to profiling cell types where cell numbers are limiting, such as rare cell types during development. A disadvantage of these methods has been the scalability and cost of the experiments, which has limited their popularity as compared with droplet-based and nanowell approaches. Here, we describe an automated protocol for full-length single-cell RNA sequencing, including both an in-house automated Smart-seq2 protocol and a commercial kit–based workflow. The protocols take 3–5 d to complete, depending on the number of plates processed in a batch. We discuss these two protocols in terms of ease of use, equipment requirements, running time, cost per sample and sequencing quality. By benchmarking the lysis buffers, reverse transcription enzymes and their combinations, we have optimized the in-house automated protocol to dramatically reduce its cost. An automated setup can be adopted easily by a competent researcher with basic laboratory skills and no prior automation experience. These pipelines have been employed successfully for several research projects allied with the Human Cell Atlas initiative (www.humancellatlas.org).},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Existing protocols for full-length single-cell RNA sequencing produce libraries of high complexity (thousands of distinct genes) with outstanding sensitivity and specificity of transcript quantification. These full-length libraries have the advantage of allowing probing of transcript isoforms, are informative regarding single-nucleotide polymorphisms and allow assembly of the VDJ region of the T- and B-cell-receptor sequences. Since full-length protocols are mostly plate-based at present, they are also suited to profiling cell types where cell numbers are limiting, such as rare cell types during development. A disadvantage of these methods has been the scalability and cost of the experiments, which has limited their popularity as compared with droplet-based and nanowell approaches. Here, we describe an automated protocol for full-length single-cell RNA sequencing, including both an in-house automated Smart-seq2 protocol and a commercial kit–based workflow. The protocols take 3–5 d to complete, depending on the number of plates processed in a batch. We discuss these two protocols in terms of ease of use, equipment requirements, running time, cost per sample and sequencing quality. By benchmarking the lysis buffers, reverse transcription enzymes and their combinations, we have optimized the in-house automated protocol to dramatically reduce its cost. An automated setup can be adopted easily by a competent researcher with basic laboratory skills and no prior automation experience. These pipelines have been employed successfully for several research projects allied with the Human Cell Atlas initiative (www.humancellatlas.org). |
W. Roberts, Leah, N. A. Harris, Patrick Integrating multiple genomic technologies to investigate an outbreak of carbapenemase-producing Enterobacter hormaechei Journal Article In: Nature Communications, 2020. @article{noKey,
title = {Integrating multiple genomic technologies to investigate an outbreak of carbapenemase-producing Enterobacter hormaechei},
author = {W. Roberts, Leah, N. A. Harris, Patrick},
url = {https://www.nature.com/articles/s41467-019-14139-5},
doi = {https://doi.org/10.1038/s41467-019-14139-5},
year = {2020},
date = {2020-01-23},
journal = {Nature Communications},
abstract = {Carbapenem-resistant Enterobacteriaceae (CRE) represent an urgent threat to human health. Here we report the application of several complementary whole-genome sequencing (WGS) technologies to characterise a hospital outbreak of blaIMP-4 carbapenemase-producing E. hormaechei. Using Illumina sequencing, we determined that all outbreak strains were sequence type 90 (ST90) and near-identical. Comparison to publicly available data linked all outbreak isolates to a 2013 isolate from the same ward, suggesting an environmental source in the hospital. Using Pacific Biosciences sequencing, we resolved the complete context of the blaIMP-4 gene on a large IncHI2 plasmid carried by all IMP-4-producing strains across different hospitals. Shotgun metagenomic sequencing of environmental samples also found evidence of ST90 E. hormaechei and the IncHI2 plasmid within the hospital plumbing. Finally, Oxford Nanopore sequencing rapidly resolved the true relationship of subsequent isolates to the initial outbreak. Overall, our strategic application of three WGS technologies provided an in-depth analysis of the outbreak.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Carbapenem-resistant Enterobacteriaceae (CRE) represent an urgent threat to human health. Here we report the application of several complementary whole-genome sequencing (WGS) technologies to characterise a hospital outbreak of blaIMP-4 carbapenemase-producing E. hormaechei. Using Illumina sequencing, we determined that all outbreak strains were sequence type 90 (ST90) and near-identical. Comparison to publicly available data linked all outbreak isolates to a 2013 isolate from the same ward, suggesting an environmental source in the hospital. Using Pacific Biosciences sequencing, we resolved the complete context of the blaIMP-4 gene on a large IncHI2 plasmid carried by all IMP-4-producing strains across different hospitals. Shotgun metagenomic sequencing of environmental samples also found evidence of ST90 E. hormaechei and the IncHI2 plasmid within the hospital plumbing. Finally, Oxford Nanopore sequencing rapidly resolved the true relationship of subsequent isolates to the initial outbreak. Overall, our strategic application of three WGS technologies provided an in-depth analysis of the outbreak. |
J. Gagen, Emma, Zaugg, Julian Goethite Reduction by a Neutrophilic Member of the Alphaproteobacterial Genus Telmatospirillum Journal Article In: Frontiers in Microbiology, 2019. @article{noKey,
title = {Goethite Reduction by a Neutrophilic Member of the Alphaproteobacterial Genus Telmatospirillum},
author = {J. Gagen, Emma, Zaugg, Julian},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2019.02938/full},
doi = {https://doi.org/10.3389/fmicb.2019.02938},
year = {2019},
date = {2019-12-19},
journal = {Frontiers in Microbiology},
abstract = {In tropical iron ore regions, biologically mediated reduction of crystalline iron oxides drives ongoing iron cycling that contributes to the stability of surface duricrusts. This represents a biotechnological opportunity with respect to post-mining rehabilitation attempts, requiring re-formation of these duricrusts. However, cultivated dissimilatory iron reducing bacteria typically reduce crystalline iron oxides quite poorly. A glucose-fermenting microbial consortium capable of reducing at least 27 mmol/L goethite was enriched from an iron duricrust region. Metagenome analysis led to the recovery of a metagenome assembled genome (MAG) of an iron reducer belonging to the alphaproteobacterial genus Telmatospirillum. This is the first report of iron reduction within the Telmatospirillum and the first reported genome of an iron-reducing, neutrophilic member of the Alphaproteobacteria. The Telmatospirillum MAG encodes putative metal transfer reductases (MtrA, MtrB) and a novel, multi-heme outer membrane cytochrome for extracellular electron transfer. In the presence of goethite, short chain fatty acid production shifted significantly in favor of acetate rather than propionate, indicating goethite is a hydrogen sink in the culture. Therefore, the presence of fermentative bacteria likely promotes iron reduction via hydrogen production. Stimulating microbial fermentation has potential to drive reduction of crystalline iron oxides, the rate limiting step for iron duricrust re-formation.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
In tropical iron ore regions, biologically mediated reduction of crystalline iron oxides drives ongoing iron cycling that contributes to the stability of surface duricrusts. This represents a biotechnological opportunity with respect to post-mining rehabilitation attempts, requiring re-formation of these duricrusts. However, cultivated dissimilatory iron reducing bacteria typically reduce crystalline iron oxides quite poorly. A glucose-fermenting microbial consortium capable of reducing at least 27 mmol/L goethite was enriched from an iron duricrust region. Metagenome analysis led to the recovery of a metagenome assembled genome (MAG) of an iron reducer belonging to the alphaproteobacterial genus Telmatospirillum. This is the first report of iron reduction within the Telmatospirillum and the first reported genome of an iron-reducing, neutrophilic member of the Alphaproteobacteria. The Telmatospirillum MAG encodes putative metal transfer reductases (MtrA, MtrB) and a novel, multi-heme outer membrane cytochrome for extracellular electron transfer. In the presence of goethite, short chain fatty acid production shifted significantly in favor of acetate rather than propionate, indicating goethite is a hydrogen sink in the culture. Therefore, the presence of fermentative bacteria likely promotes iron reduction via hydrogen production. Stimulating microbial fermentation has potential to drive reduction of crystalline iron oxides, the rate limiting step for iron duricrust re-formation. |
X. Rwandamuriye, Francois, Chopra, Abha A Rapid Allele-Specific Assay for HLA-A*32:01 to Identify Patients at Risk for Vancomycin-Induced Drug Reaction with Eosinophilia and Systemic Symptoms Journal Article In: The Journal of Molecular Diagnostics, 2019. @article{noKey,
title = {A Rapid Allele-Specific Assay for HLA-A*32:01 to Identify Patients at Risk for Vancomycin-Induced Drug Reaction with Eosinophilia and Systemic Symptoms},
author = {X. Rwandamuriye, Francois, Chopra, Abha},
url = {https://www.jmdjournal.org/article/S1525-1578(19)30076-5/fulltext},
doi = {https://doi.org/10.1016/j.jmoldx.2019.04.006},
year = {2019},
date = {2019-08-31},
journal = {The Journal of Molecular Diagnostics},
abstract = {Human leukocyte antigen (HLA) alleles have been implicated as risk factors for immune-mediated adverse drug reactions. The authors recently reported a strong association between HLA-A*32:01 and vancomycin-induced drug reaction with eosinophilia and systemic symptoms. Identification of individuals with the risk allele before or shortly after the initiation of vancomycin therapy is of great clinical importance to prevent morbidity and mortality, and improve drug safety and antibiotic treatment options. A prerequisite to the success of pharmacogenetic screening tests is the development of simple, robust, cost-effective single HLA allele test that can be implemented in routine diagnostic laboratories. In this study, the authors developed a simple, real-time allele-specific PCR for typing the HLA-A*32:01 allele. Four-hundred and fifty-eight DNA samples including 30 HLA-A*32:01–positive samples were typed by allele-specific PCR. Compared with American Society for Histocompatibility and Immunogenetics–accredited, sequence-based, high-resolution, full-allelic HLA typing, this assay demonstrates 100% accuracy, 100% sensitivity (95% CI, 88.43% to 100%), and 100% specificity (95% CI, 99.14% to 100%). The lowest limit of detection of this assay using PowerUp SYBR Green is 10 ng of template DNA. The assay demonstrates a sensitivity and specificity to differentiate the HLA-A*32:01 allele from closely related non–HLA-A*32 alleles and may be used in clinical settings to identify individuals with the risk allele before or during the course of vancomycin therapy.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Human leukocyte antigen (HLA) alleles have been implicated as risk factors for immune-mediated adverse drug reactions. The authors recently reported a strong association between HLA-A*32:01 and vancomycin-induced drug reaction with eosinophilia and systemic symptoms. Identification of individuals with the risk allele before or shortly after the initiation of vancomycin therapy is of great clinical importance to prevent morbidity and mortality, and improve drug safety and antibiotic treatment options. A prerequisite to the success of pharmacogenetic screening tests is the development of simple, robust, cost-effective single HLA allele test that can be implemented in routine diagnostic laboratories. In this study, the authors developed a simple, real-time allele-specific PCR for typing the HLA-A*32:01 allele. Four-hundred and fifty-eight DNA samples including 30 HLA-A*32:01–positive samples were typed by allele-specific PCR. Compared with American Society for Histocompatibility and Immunogenetics–accredited, sequence-based, high-resolution, full-allelic HLA typing, this assay demonstrates 100% accuracy, 100% sensitivity (95% CI, 88.43% to 100%), and 100% specificity (95% CI, 99.14% to 100%). The lowest limit of detection of this assay using PowerUp SYBR Green is 10 ng of template DNA. The assay demonstrates a sensitivity and specificity to differentiate the HLA-A*32:01 allele from closely related non–HLA-A*32 alleles and may be used in clinical settings to identify individuals with the risk allele before or during the course of vancomycin therapy. |
Džunková, Mária, Low, Soo Jen Defining the human gut host–phage network through single-cell viral tagging Journal Article In: Nature Microbiology, 2019. @article{noKey,
title = {Defining the human gut host–phage network through single-cell viral tagging},
author = {Džunková, Mária, Low, Soo Jen},
url = {https://www.nature.com/articles/s41564-019-0526-2},
doi = {https://doi.org/10.1038/s41564-019-0526-2},
year = {2019},
date = {2019-08-04},
journal = {Nature Microbiology},
abstract = {Viral discovery is accelerating at an unprecedented rate due to continuing advances in culture-independent sequence-based analyses. One important facet of this discovery is identification of the hosts of these recently characterized uncultured viruses. To this end, we have adapted the viral tagging approach, which bypasses the need for culture-based methods to identify host–phage pairings. Fluorescently labelled anonymous virions adsorb to unlabelled anonymous bacterial host cells, which are then individually sorted as host–phage pairs, followed by genome amplification and high-throughput sequencing to establish the identities of both the host and the attached virus(es). We demonstrate single-cell viral tagging using the faecal microbiome, including cross-tagging of viruses and bacteria between human subjects. A total of 363 unique host–phage pairings were predicted, most of which were subject-specific and involved previously uncharacterized viruses despite the majority of their bacterial hosts having known taxonomy. One-fifth of these pairs were confirmed by multiple individual tagged cells. Viruses targeting more than one bacterial species were conspicuously absent in the host–phage network, suggesting that phages are not major vectors of inter-species horizontal gene transfer in the human gut. A high level of cross-reactivity between phages and bacteria from different subjects was noted despite subject-specific viral profiles, which has implications for faecal microbiota transplant therapy.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Viral discovery is accelerating at an unprecedented rate due to continuing advances in culture-independent sequence-based analyses. One important facet of this discovery is identification of the hosts of these recently characterized uncultured viruses. To this end, we have adapted the viral tagging approach, which bypasses the need for culture-based methods to identify host–phage pairings. Fluorescently labelled anonymous virions adsorb to unlabelled anonymous bacterial host cells, which are then individually sorted as host–phage pairs, followed by genome amplification and high-throughput sequencing to establish the identities of both the host and the attached virus(es). We demonstrate single-cell viral tagging using the faecal microbiome, including cross-tagging of viruses and bacteria between human subjects. A total of 363 unique host–phage pairings were predicted, most of which were subject-specific and involved previously uncharacterized viruses despite the majority of their bacterial hosts having known taxonomy. One-fifth of these pairs were confirmed by multiple individual tagged cells. Viruses targeting more than one bacterial species were conspicuously absent in the host–phage network, suggesting that phages are not major vectors of inter-species horizontal gene transfer in the human gut. A high level of cross-reactivity between phages and bacteria from different subjects was noted despite subject-specific viral profiles, which has implications for faecal microbiota transplant therapy. |
Schaum, Nicholas, Karkanias, Jim Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris Journal Article In: Nature, 2018. @article{noKey,
title = {Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris},
author = {Schaum, Nicholas, Karkanias, Jim},
url = {https://www.nature.com/articles/s41586-018-0590-4},
doi = {https://doi.org/10.1038/s41586-018-0590-4},
year = {2018},
date = {2018-10-02},
journal = {Nature},
abstract = {Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3′-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.},
keywords = {Mantis®},
pubstate = {published},
tppubtype = {article}
}
Here we present a compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3′-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology. |
