Ultra-sensitive nanoLC-MS using second generation micro pillar array LC technology with Orbitrap Exploris 480 and FAIMS PRO to enable single cell proteomics

ABSTRACTIn the light of the ongoing single-cell revolution, scientific disciplines are combining forces to retrieve as much relevant data as possible from trace amounts of biological material. For single cell proteomics, this implies optimizing the entire workflow from initial cell isolation down to sample preparation, liquid chromatography (LC) separation, mass spectrometer (MS) data acquisition and data analysis. To demonstrate the potential for single cell and limited sample proteomics, we report on a series of benchmarking experiments where we combine LC separation on a new generation of micro pillar array columns with state-of-the-art Orbitrap MS/MS detection and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS). This dedicated limited sample column has a reduced cross section and micro pillar dimensions that have been further downscaled (inter pillar distance and pillar diameter by a factor of 2), resulting in improved chromatography at reduced void times. A dilution series of a HeLa tryptic digest (5-0.05 ng/μL) was used to explore the sensitivity that can be achieved. Comparative processing of the MS/MS data with Sequest HT, MS Amanda, Mascot and SpectroMine pointed out the benefits of using Sequest HT together with INFERYS when analyzing samples amounts below 1 ng. 2855 proteins were identified from just 1 ng of HeLa lysate, hereby increasing detection sensitivity as compared to a previous contribution by a factor well above 10. By successfully identifying 1486 proteins from as little as 250 pg of HeLa tryptic digest, we demonstrate outstanding sensitivity with great promise for use in limited sample proteomics workflows.

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Single-cell analysis for drug development using convex lens-induced confinement imaging

BioTechniques ◽

10.2144/btn-2019-0067 ◽

2019 ◽

Vol 67 (5) ◽

pp. 210-217 ◽

Cited By ~ 1

Author(s):

Ndeye Khady Thiombane ◽

Nicolas Coutin ◽

Daniel Berard ◽

Radin Tahvildari ◽

Sabrina Leslie ◽

...

Keyword(s):

Single Cell ◽

Drug Response ◽

Drug Exposure ◽

Cellular Proliferation ◽

New Technologies ◽

Detection Sensitivity ◽

Yeast Cells ◽

Sample Population ◽

Phenotypic Analysis ◽

Convex Lens

New technologies have powered rapid advances in cellular imaging, genomics and phenotypic analysis in life sciences. However, most of these methods operate at sample population levels and provide statistical averages of aggregated data that fail to capture single-cell heterogeneity, complicating drug discovery and development. Here we demonstrate a new single-cell approach based on convex lens-induced confinement (CLiC) microscopy. We validated CLiC on yeast cells, demonstrating subcellular localization with an enhanced signal-to-noise and fluorescent signal detection sensitivity compared with traditional imaging. In the live-cell CLiC assay, cellular proliferation times were consistent with flask culture. Using methotrexate, we provide drug response data showing a fivefold cell size increase following drug exposure. Taken together, CLiC enables high-quality imaging of single-cell drug response and proliferation for extended observation periods.

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Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽

10.1186/s12864-020-07358-4 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Tracy M. Yamawaki ◽

Daniel R. Lu ◽

Daniel C. Ellwanger ◽

Dev Bhatt ◽

Paolo Manzanillo ◽

...

Keyword(s):

Single Cell ◽

High Throughput ◽

Immune Cell ◽

Cell Types ◽

Data Interpretation ◽

Detection Sensitivity ◽

Rna Seq ◽

Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

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Single cell transcriptomic analysis of diffuse large B cells in cerebrospinal fluid of central nervous system lymphoma

10.1101/2020.04.18.20065805 ◽

2020 ◽

Author(s):

Haoyu Ruan ◽

Zhe Wang ◽

Yue Zhai ◽

Ying Xu ◽

Linyu Pi ◽

...

Keyword(s):

Central Nervous System ◽

Cerebrospinal Fluid ◽

Nervous System ◽

B Cells ◽

B Cell ◽

Single Cell ◽

Central Nervous System Lymphoma ◽

B Cell Lymphoma ◽

Great Promise ◽

Leptomeningeal Involvement

AbstractDiffuse large B-cell lymphoma (DLBCL) is the predominant type of central nervous system lymphoma (CNSL) including primary CNSL and secondary CNSL. Diffuse large B cells in cerebrospinal fluid (CSF-DLBCs) have offered great promise for the diagnostics and therapeutics of CNSL leptomeningeal involvement. To explore the distinct phenotypic states of CSF-DLBCs, we analyzed the transcriptomes of 902 CSF-DLBCs from six CNSL-DLBCL patients using single-cell RNA sequencing technology. We defined CSF-DLBCs based on abundant expression of B-cell markers, as well as the enrichment of cell proliferation and energy metabolism pathways. CSF-DLBCs within individual patients exhibited monoclonality with similar variable region of light chains (VL) expression. It is noteworthy that we observed some CSF-DLBCs have double classes of VL (lambda and kappa) transcripts. We identified substantial heterogeneity in CSF-DLBCs, and found significantly greater among-patient heterogeneity compared to among-cell heterogeneity within a given patient. The transcriptional heterogeneity across CSF-DLBCs is manifested in cell cycle state and cancer-testis antigens expression. Our results will provide insight into the mechanism research and new diagnostic direction of CNSL-DLBCL leptomeningeal involvement.

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Circulating tumor cell characterization of lung cancer brain metastasis in the cerebrospinal fluid through single-cell transcriptome analysis

10.1101/2020.01.06.20016683 ◽

2020 ◽

Author(s):

Haoyu Ruan ◽

Yihang Zhou ◽

Jie Shen ◽

Yue Zhai ◽

Ying Xu ◽

...

Keyword(s):

Lung Cancer ◽

Cerebrospinal Fluid ◽

Single Cell ◽

Tumor Cells ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Unknown Primary ◽

Great Promise ◽

Cell Cycle Gene

AbstractMetastatic lung cancer accounts for about half of the brain metastases (BM). Development of leptomeningeal metastases (LM) are becoming increasingly common, and its prognosis is still poor despite the advances in systemic and local approaches. Cytology analysis in the cerebrospinal fluid (CSF) remains the diagnostic gold standard. Although several previous studies performed in CSF have offered great promise for the diagnostics and therapeutics of LM, a comprehensive characterization of circulating tumor cells (CTCs) in CSF is still lacking. To fill this critical gap of lung adenocarcinoma LM (LUAD-LM), we analyzed the transcriptomes of 1,375 cells from 5 LUAD-LM patient and 3 control samples using single-cell RNA sequencing technology. We defined CSF-CTCs based on abundant expression of epithelial markers and genes with lung origin, as well as the enrichment of metabolic pathway and cell adhesion molecules, which are crucial for the survival and metastases of tumor cells. Elevated expression of CEACAM6 and SCGB3A2 was discovered in CSF-CTCs, which could serve as candidate biomarkers of LUAD-LM. We identified substantial heterogeneity in CSF-CTCs among LUAD-LM patients and within patient among individual cells. Cell-cycle gene expression profiles and the proportion of CTCs displaying mesenchymal and cancer stem cell properties also vary among patients. In addition, CSF-CTC transcriptome profiling identified one LM case as cancer of unknown primary site (CUP). Our results will shed light on the mechanism of LUAD-LM and provide a new direction of diagnostic test of LUAD-LM and CUP cases from CSF samples.

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μCB-seq: Microfluidic cell barcoding and sequencing for high-resolution imaging and sequencing of single cells

10.1101/2020.02.18.954974 ◽

2020 ◽

Author(s):

Tyler N. Chen ◽

Anushka Gupta ◽

Mansi Zalavadia ◽

Aaron M. Streets

Keyword(s):

High Resolution ◽

Single Cell ◽

Single Cell Analysis ◽

Protein Localization ◽

Single Cells ◽

Optical Measurements ◽

Detection Sensitivity ◽

High Resolution Imaging ◽

Cell Analysis ◽

Resolution Imaging

AbstractSingle-cell RNA sequencing (scRNA-seq) enables the investigation of complex biological processes in multicellular organisms with high resolution. However, many phenotypic features that are critical to understanding the functional role of cells in a heterogeneous tissue or organ are not directly encoded in the genome and therefore cannot be profiled with scRNA-seq. Quantitative optical microscopy has long been a powerful approach for characterizing diverse cellular phenotypes including cell morphology, protein localization, and chemical composition. Combining scRNA-seq with optical imaging has the potential to provide comprehensive single-cell analysis, allowing for functional integration of gene expression profiling and cell-state characterization. However, it is difficult to track single cells through both measurements; therefore, coupling current scRNA-seq protocols with optical measurements remains a challenge. Here, we report Microfluidic Cell Barcoding and Sequencing (μCB-seq), a microfluidic platform that combines high-resolution imaging and sequencing of single cells. μCB-seq is enabled by a novel fabrication method that preloads primers with known barcode sequences inside addressable reaction chambers of a microfluidic device. In addition to enabling multi-modal single-cell analysis, μCB-seq improves gene detection sensitivity, providing a scalable and accurate method for information-rich characterization of single cells.

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AIE Active Polyelectrolyte Based Photosensitizers: The Effects of Structure on Antibiotic-Resistant Bacterial Sensing and Killing, and Pollutant Decomposition

Journal of Materials Chemistry B ◽

10.1039/d1tb00939g ◽

2021 ◽

Author(s):

Hui Xie ◽

Wanshan Hu ◽

Fei Zhang ◽

Changbo Zhao ◽

Tingting Peng ◽

...

Keyword(s):

Antibacterial Activity ◽

Detection Sensitivity ◽

Bacteria Detection ◽

Great Promise ◽

Antibiotic Resistant ◽

Dye Decomposition ◽

Good Antibacterial Activity ◽

Bacterial Sensing ◽

Decomposition Efficiency ◽

Multifunctional Platform

A facile and effective multifunctional platform with high bacteria detection sensitivity, good antibacterial activity, and excellent dye decomposition efficiency holds great promise for wastewater treatment. To explore design rationality and...

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scHinter: imputing dropout events for single-cell RNA-seq data with limited sample size

Bioinformatics ◽

10.1093/bioinformatics/btz627 ◽

2019 ◽

Author(s):

Pengchao Ye ◽

Wenbin Ye ◽

Congting Ye ◽

Shuchao Li ◽

Lishan Ye ◽

...

Keyword(s):

Gene Expression ◽

Sample Size ◽

Single Cell ◽

Wide Spectrum ◽

Dropout Rate ◽

Supplementary Information ◽

Sample Sizes ◽

Limited Sample ◽

Limited Sample Size ◽

The Impact

Abstract Motivation Single-cell RNA-sequencing (scRNA-seq) is fast and becoming a powerful technique for studying dynamic gene regulation at unprecedented resolution. However, scRNA-seq data suffer from problems of extremely high dropout rate and cell-to-cell variability, demanding new methods to recover gene expression loss. Despite the availability of various dropout imputation approaches for scRNA-seq, most studies focus on data with a medium or large number of cells, while few studies have explicitly investigated the differential performance across different sample sizes or the applicability of the approach on small or imbalanced data. It is imperative to develop new imputation approaches with higher generalizability for data with various sample sizes. Results We proposed a method called scHinter for imputing dropout events for scRNA-seq with special emphasis on data with limited sample size. scHinter incorporates a voting-based ensemble distance and leverages the synthetic minority oversampling technique for random interpolation. A hierarchical framework is also embedded in scHinter to increase the reliability of the imputation for small samples. We demonstrated the ability of scHinter to recover gene expression measurements across a wide spectrum of scRNA-seq datasets with varied sample sizes. We comprehensively examined the impact of sample size and cluster number on imputation. Comprehensive evaluation of scHinter across diverse scRNA-seq datasets with imbalanced or limited sample size showed that scHinter achieved higher and more robust performance than competing approaches, including MAGIC, scImpute, SAVER and netSmooth. Availability and implementation Freely available for download at https://github.com/BMILAB/scHinter. Supplementary information Supplementary data are available at Bioinformatics online.

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The potential impact of new generation molecular point-of-care tests on gonorrhoea and chlamydia in a setting of high endemic prevalence

Sexual Health ◽

10.1071/sh13026 ◽

2013 ◽

Vol 10 (4) ◽

pp. 348 ◽

Cited By ~ 22

Author(s):

Ben B. Hui ◽

David P. Wilson ◽

James S. Ward ◽

Rebecca J. Guy ◽

John M. Kaldor ◽

...

Keyword(s):

Point Of Care ◽

Treatment Strategies ◽

High Sensitivity ◽

Indigenous Communities ◽

Great Promise ◽

Screening Methods ◽

Sexually Transmissible Infections ◽

Screening Coverage ◽

New Generation ◽

The Impact

Background Despite the availability of testing and treatment, bacterial sexually transmissible infections (STIs) continue to occur at endemic levels in many remote Indigenous communities in Australia. New generation molecular point-of-care (POC) tests have high sensitivity, comparable with conventional diagnostic tests, and have the potential to increase the impact of STI screening. Methods: We developed mathematical models of gonorrhoea (Neisseria gonorrhoeae) and chlamydia (Chlamydia trachomatis) transmission in remote Indigenous communities in Australia to evaluate screening and treatment strategies that utilise POC tests. Results: The introduction of POC testing with 95% sensitivity could reduce the prevalence of gonorrhoea and chlamydia from 7.1% and 11.9% to 5.7% and 8.9%, respectively, under baseline screening coverage of 44% per year. If screening coverage is increased to 60% per year, prevalence is predicted to be reduced to 3.6% and 6.7%, respectively, under conventional testing, and further reduced to 1.8% and 3.1% with the introduction of POC testing. Increasing screening coverage to 80% per year will result in a reduction in the prevalence of gonorrhoea and chlamydia to 0.6% and 1.5%, respectively, and the virtual elimination of both STIs if POC testing is introduced. Conclusions: Modelling suggests that molecular POC tests of high sensitivity have great promise as a public health strategy for controlling chlamydia and gonorrhoea. However, evaluation of the cost-effectiveness of POC testing needs to be made before widespread implementation of this technology can be considered.

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Genome-wide association studies: a powerful tool for neurogenomics

Neurosurgical FOCUS ◽

10.3171/2010.10.focus09186 ◽

2010 ◽

Vol 28 (1) ◽

pp. E2 ◽

Cited By ~ 5

Author(s):

Matthew C. Cowperthwaite ◽

Deepankar Mohanty ◽

Mark G. Burnett

Keyword(s):

Neurological Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Great Promise ◽

Genome Wide Association Studies ◽

Entire Genome ◽

Genome Wide ◽

New Generation ◽

Theoretical Issues ◽

Gwa Studies

As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.

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Revealing Antibiotic-Tolerance of the Mycobacterium smegmatis Xanthine/Uracil Permease Mutant Using Microfluidics and Single-Cell Analysis

10.20944/preprints202106.0052.v1 ◽

2021 ◽

Author(s):

Meltem Elitas ◽

Neeraj Dhar ◽

John McKinney

Keyword(s):

Single Cell ◽

Mycobacterium Smegmatis ◽

Single Cell Analysis ◽

Sampling Rate ◽

Nitrogen Compound ◽

Great Promise ◽

Antibiotic Tolerance ◽

Wild Type ◽

Gene Encoding ◽

Bacterial Populations

To reveal rare phenotypes in bacterial populations conventional microbiology tools should be advanced to generate rapid, quantitative, accurate and high-throughput data. The main drawbacks of widely used traditional methods for antibiotic studies include low sampling rate and averaging data for population measurements. To overcome these limitations microfluidic-microscopy systems have great promise to produce quantitative single-cell data with high sampling rates. Using Mycobacterium smegmatis cells we applied both conventional assays and a microfluidic-microscopy method to reveal antibiotic-tolerance mechanisms of wild type and the msm2570::Tnmutant cells. Our results revealed that the enhanced antibiotic tolerance mechanism of the msm2570::Tn mutant was due to the low number of lysed cells during the antibiotic exposure compared with wild-type cells. This is the first study that characterized the antibiotic-tolerance phenotype of the msm2570::Tn mutant that has a transposon insertion in the msm2570 gene encoding a putative xanthine/uracil permease, which enrolls in uptake of nitrogen compound during nitrogen limitation. The experimental results indicate that the msm2570::Tn mutant can be further interrogated to reveal antibiotic killing mechanisms, in particularly, antibiotics those targets cell wall integrity.

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