Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

Background: Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results: We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion: Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis.</p

Comparison of Single Cell Transcriptome Sequencing Methods:Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.</p

Unraveling the impact of AXIN1 mutations on HCC development:Insights from CRISPR/Cas9 repaired AXIN1-mutant liver cancer cell lines

Background Hepatocellular carcinoma (HCC) is a highly aggressive liver cancer with significant morbidity and mortality rates. AXIN1 is one of the top-mutated genes in HCC, but the mechanism by which AXIN1 mutations contribute to HCC development remains unclear. Methods In this study, we utilized CRISPR/Cas9 genome editing to repair AXIN1-truncated mutations in five HCC cell lines. Results For each cell line we successfully obtained 2-4 correctly repaired clones, which all show reduced β-catenin signaling accompanied with reduced cell viability and colony formation. Although exposure of repaired clones to Wnt3A-conditioned medium restored β-catenin signaling, it did not or only partially recover their growth characteristics, indicating the involvement of additional mechanisms. Through RNA-sequencing analysis, we explored the gene expression patterns associated with repaired AXIN1 clones. Except for some highly-responsive β-catenin target genes, no consistent alteration in gene/pathway expression was observed. This observation also applies to the Notch and YAP/TAZ-Hippo signaling pathways, which have been associated with AXIN1-mutant HCCs previously. The AXIN1-repaired clones also cannot confirm a recent observation that AXIN1 is directly linked to YAP/TAZ protein stability and signaling. Conclusions Our study provides insights into the effects of repairing AXIN1 mutations on β-catenin signaling, cell viability, and colony formation in HCC cell lines. However, further investigations are necessary to understand the complex mechanisms underlying HCC development associated with AXIN1 mutations.</p

Herd-level animal management factors associated with the occurrence of bovine neonatal pancytopenia in calves in a multicountry study

Since 2007, mortality associated with a previously unreported haemorrhagic disease has been observed in young calves in several European countries. The syndrome, which has been named ‘bovine neonatal pancytopenia’ (BNP), is characterised by thrombocytopenia, leukocytopenia and a panmyelophthisis. A herd-level case-control study was conducted in four BNP affected countries (Belgium, France, Germany and the Netherlands) to identify herd management risk factors for BNP occurrence. Data were collected using structured face-to-face and telephone interviews of farm managers and their local veterinarians. In total, 363 case farms and 887 control farms were included in a matched multivariable conditional logistic regression analysis. Case-control status was strongly associated with the odds of herd level use of the vaccine PregSure® BVD (PregSure, Pfizer Animal Health) (matched adjusted odds ratio (OR) 107.2; 95% CI: 41.0–280.1). This was also the case for the practices of feeding calves colostrum from the calf’s own dam (OR 2.0; 95% CI: 1.1–3.4) or feeding pooled colostrum (OR 4.1; 95% CI: 1.9–8.8). Given that the study had relatively high statistical power and represented a variety of cattle production and husbandry systems, it can be concluded with some confidence that no other herd level management factors are competent causes for a sufficient cause of BNP occurrence on herd level. It is suggested that genetic characteristics of the dams and BNP calves should be the focus of further investigations aimed at identifying the currently missing component causes that together with PregSure vaccination and colostrum feeding represent a sufficient cause for occurrence of BNP in calves

Histological and serological features of acute liver injury after SARS-CoV-2 vaccination

Codoni G, Kirchner T, Engel B, Villamil AM, Efe C, Stättermayer AF, Weltzsch JP, Sebode M, Bernsmeier C, Lleo A, Gevers TJ, Kupčinskas L, Castiella A, Pinazo J, De Martin E, Bobis I, Sandahl TD, Pedica F, Invernizzi F, Del Poggio P, Bruns T, Kolev M, Semmo N, Bessone F, Giguet B, Poggi G, Ueno M, Jang H, Elpek GÖ, Soylu NK, Cerny A, Wedemeyer H, Vergani D, Mieli-Vergani G, Lucena MI, Andrade RJ, Zen Y, Taubert R, Beretta-Piccoli BT, Histological and serological features of acute liver injury after SARS-CoV-2 vaccination, JHEP Reports (2022), doi: https://doi.org/10.1016/j.jhepr.2022.100605.Liver injury with autoimmune features after vaccination against Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2) is increasingly reported. We investigated a large international cohort of patients with acute hepatitis arising after SARS-CoV-2 vaccination, focusing on histological and serological features

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Split Pool Ligation-based Single-cell Transcriptome sequencing (SPLiT-seq) data processing pipeline comparison

Background: Single-cell sequencing techniques are revolutionizing every field of biology by providing the ability to measure the abundance of biological molecules at a single-cell resolution. Although single-cell sequencing approaches have been developed for several molecular modalities, single-cell transcriptome sequencing is the most prevalent and widely applied technique. SPLiT-seq (split-pool ligation-based transcriptome sequencing) is one of these single-cell transcriptome techniques that applies a unique combinatorial-barcoding approach by splitting and pooling cells into multi-well plates containing barcodes. This unique approach required the development of dedicated computational tools to preprocess the data and extract the count matrices. Here we compare eight bioinformatic pipelines (alevin-fry splitp, LR-splitpipe, SCSit, splitpipe, splitpipeline, SPLiTseq-demultiplex, STARsolo and zUMI) that have been developed to process SPLiT-seq data. We provide an overview of the tools, their computational performance, functionality and impact on downstream processing of the single-cell data, which vary greatly depending on the tool used. Results: We show that STARsolo, splitpipe and alevin-fry splitp can all handle large amount of data within reasonable time. In contrast, the other five pipelines are slow when handling large datasets. When using smaller dataset, cell barcode results are similar with the exception of SPLiTseq-demultiplex and splitpipeline. LR-splitpipe that is originally designed for processing long-read sequencing data is the slowest of all pipelines. Alevin-fry produced different down-stream results that are difficult to interpret. STARsolo functions nearly identical to splitpipe and produce results that are highly similar to each other. However, STARsolo lacks the function to collapse random hexamer reads for which some additional coding is required. Conclusion: Our comprehensive comparative analysis aids users in selecting the most suitable analysis tool for efficient SPLiT-seq data processing, while also detailing the specific prerequisites for each of these pipelines. From the available pipelines, we recommend splitpipe or STARSolo for SPLiT-seq data analysis.</p

Comparison of Single Cell Transcriptome Sequencing Methods:Of Mice and Men

Single cell RNAseq has been a big leap in many areas of biology. Rather than investigating gene expression on a whole organism level, this technology enables scientists to get a detailed look at rare single cells or within their cell population of interest. The field is growing, and many new methods appear each year. We compared methods utilized in our core facility: Smart-seq3, PlexWell, FLASH-seq, VASA-seq, SORT-seq, 10X, Evercode, and HIVE. We characterized the equipment requirements for each method. We evaluated the performances of these methods based on detected features, transcriptome diversity, mitochondrial RNA abundance and multiplets, among others and benchmarked them against bulk RNA sequencing. Here, we show that bulk transcriptome detects more unique transcripts than any single cell method. While most methods are comparable in many regards, FLASH-seq and VASA-seq yielded the best metrics, e.g., in number of features. If no equipment for automation is available or many cells are desired, then HIVE or 10X yield good results. In general, more recently developed methods perform better. This also leads to the conclusion that older methods should be phased out, and that the development of single cell RNAseq methods is still progressing considerably.</p

Impact of pre-stroke dependency on outcome after endovascular therapy in acute ischemic stroke.

BACKGROUND AND PURPOSE Current demographic changes indicate that more people will be care-dependent due to increasing life expectancy. Little is known about impact of preexisting dependency on stroke outcome after endovascular treatment (EVT). METHODS We compared prospectively collected baseline and outcome data of previously dependent vs. independent stroke patients (prestroke modified Rankin Scale score of 3-5 vs. 0-2) treated with EVT. Outcome measures were favorable 3-month outcome (mRS ≤ 3 for previously dependent and mRS ≤ 2 for independent patients, respectively), death and symptomatic intracranial hemorrhage (sICH). RESULTS Among 1247 patients, 84 (6.7%) were dependent before stroke. They were older (81 vs. 72 years of age), more often female (61.9% vs. 46%), had a higher stroke severity at baseline (NIHSS 18 vs. 15 points), more often history of previous stroke (32.9% vs. 9.1%) and more vascular risk factors than independent patients. Favorable outcome and mortality were to the disadvantage of independent patients (26.2% vs. 44.4% and 46.4% vs. 25.5%, respectively), whereas sICH was comparable in both cohorts (4.9% vs. 5%). However, preexisting dependency was not associated with clinical outcome and mortality after adjusting for outcome predictors (OR 1.076, 95% CI 0.612-1.891; p = 0.799 and OR 1.267, 95% CI 0.758-2.119; p = 0.367, respectively). CONCLUSION Our study underscores the need for careful selection of care-dependent stroke patients when considering EVT, given a less favorable outcome observed in this cohort. Nonetheless, EVT should not systematically be withheld in patients with preexisting disability, since prior dependency does not significantly influence outcome