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Blainey, P. C.

Publications and source records attributed to Blainey, P. C..

29 records · Page 2Linked to original sources

Consensus transcriptional states describe human mononuclear phagocyte diversity in the lung across health and disease

Monocytes, dendritic cells, and macrophages, commonly referred to as mononuclear phagocytes (MNPs), are innate immune cells capable of adopting diverse homeostatic and pathogenic phenotypes. Recent single-cell RNA-sequencing studies across many diseases in the lung have profiled this diversity transcriptionally, defining new cellular states and their association with disease. Despite these massive cellular profiling efforts, many studies have focused on defining myeloid dysfunction in specific diseases without identifying common pan-disease trends in the mononuclear phagocyte compartment within the lung. To address these gaps in our knowledge, we collate, process, and analyze 561,390 cellular transcriptomes from 12 studies of the human lung across multiple human diseases. We develop a computational framework to identify and compare dominant gene markers and gene expression programs and characterize MNP diversity in the lung, proposing a conserved dictionary of gene sets. Utilizing this reference, we efficiently identify disease-associated and rare MNP populations across multiple diseases and cohorts. Furthermore, we demonstrate the utility of this dictionary in characterizing a recently published dataset of bronchoalveolar lavage cells from COVID-19 patients and healthy controls which further reveal novel transcriptional shifts directly relatable to other diseases in the lung. These results underline conserved MNP transcriptional programs in lung disease, provide an immediate reference for characterizing the landscape of lung MNPs and establish a roadmap to dissecting MNP transcriptional complexity across tissues.

immunology↗

NickSeq for genome-wide strand-specific identification of DNA single-strand break sites with single nucleotide resolution

DNA single-strand breaks (SSBs), or nicks, are the most common form of DNA damage. Nicks occur at rates of tens of thousands per cell per day, and result from many sources including oxidative stress and endogenous enzyme activities. Accumulation of nicks, due to high rates of occurrence or defects in repair enzymes, has been implicated in multiple diseases. However, improved methods for nick analysis are needed to learn how their locations and number affect cells, disease progression, and health outcomes. In addition to natural processes including DNA repair, leading genome-editing technologies rely on nuclease activity, including nick generation, at target sites. There is currently a pressing need for methods to study unintended nicking activity genome-wide to evaluate the impact of emerging genome editing tools on cells and organisms. Here we developed a new method, NickSeq, for efficient strand-specific profiling of nicks in complex DNA samples with single nucleotide resolution and low false-positive rates. NickSeq produces deep sequence datasets enriched for reads near nick sites and establishes a readily detectable mutational signal that allows for determination of the nick site and strand. In this work, we apply NickSeq to profile off-target activity of the Nb.BsmI nicking endonuclease and an engineered spCas9 nickase. NickSeq will be useful in exploring the relevance of spontaneously occurring or repair-induced DNA breaks in human disease, DNA breaks caused by DNA damaging agents including therapeutics, and the activity of engineered nucleases in genome editing and other biotechnological applications.

genomics↗

Somatic Truth Data from Cell Lineage

Existing somatic benchmark datasets for human sequencing data use germline variants, synthetic methods, or expensive validations, none of which are satisfactory for providing a large collection of true somatic variation across a whole genome. Here we propose a dataset of short somatic mutations, that are validated using a known cell lineage. The dataset contains 56,974 (2,687 unique) Single Nucleotide Variations (SNV), 6,370 (316 unique) small Insertions and Deletions (Indels), and 144 (8 unique) Copy Number Variants (CNV) across 98 in silico mixed truth sets with a high confidence region covering 2.7 gigabases per mixture. The data is publicly available for use as a benchmarking dataset for somatic short mutation discovery pipelines.

bioinformatics↗

Nucleic Acid Cleavage with a Hyperthermophilic Cas9 from an Unculturable Ignavibacterium

CRISPR-Cas9 systems have been effectively harnessed to engineer the genomes of organisms from across the tree of life. Nearly all currently characterized Cas9 proteins are derived from mesophilic bacteria, and canonical Cas9 systems are challenged by applications requiring enhanced stability or elevated temperatures. We discovered IgnaviCas9, a Cas9 protein from a hyperthermophilic Ignavibacterium identified through mini-metagenomic sequencing of samples from a hot spring. IgnaviCas9 is active at temperatures up to 100 {degrees}C in vitro, which enables DNA cleavage beyond the 44 {degrees}C limit of Streptococcus pyogenes Cas9 (SpyCas9) and the 70 {degrees}C limit of both Geobacillus stearothermophilus Cas9 (GeoCas9) and Geobacillus thermodenitrificans T12 Cas9 (ThermoCas9). As a potential application of this enzyme, we demonstrated that IgnaviCas9 can be used in bacterial RNA-seq library preparation to remove unwanted cDNA from 16s ribosomal rRNA (rRNA) without increasing the number of steps, thus underscoring the benefits provided by its exceptional thermostability in improving molecular biology and genomic workflows. Taken together, IgnaviCas9 is an exciting addition to the CRISPR-Cas9 toolbox and expands its temperature range.

genomics↗

Hydrogenotrophic methanogenesis in archaeal phylum Verstraetearchaeota reveals the shared ancestry of all methanogens

Methanogenic archaea are major contributors to the global carbon cycle and were long thought to belong exclusively to the euryarchaeotal phylum. Discovery of the methanogenesis gene cluster methyl-coenzyme M reductase (Mcr) in the Bathyarchaeota and thereafter the Verstraetearchaeota led to a paradigm shift, pushing back the evolutionary origin of methanogenesis to pre-date that of the Euryarchaeota. The methylotrophic methanogenesis found in the non-Euryarchaota distinguished itself from the predominantly hydrogenotrophic methanogens found in euryarchaeal orders as the former do not couple methanogenesis to carbon fixation through the reductive acetyl-coenzyme A (Wood-Ljungdahl) pathway, which was interpreted as evidence for independent evolution of the two methanogenesis pathways. Here, we report the discovery of a complete and divergent hydrogenotrophic methanogenesis pathway in a novel, thermophilic order of the Verstraetearchaeota which we have named Candidatus Methanohydrogenales, as well as the presence of the Wood-Ljungdahl pathway in the crenarchaeal order Desulfurococcales. Our findings support the ancient origin of hydrogenotrophic methanogenesis, suggest that methylotrophic methanogenesis might be a later adaptation of specific orders, and provide insight into how transition from hydrogenotrophic to methylotrophic methanogenesis might occur.

microbiology↗

Lentiviral co-packaging mitigates the effects of intermolecular recombination and multiple integrations in pooled genetic screens

Lentiviral vectors are widely used for functional genomic screens, enabling efficient and stable transduction of target cells with libraries of genetic elements. Unfortunately, designs that rely on integrating multiple variable sequences, such as combinatorial perturbations or perturbations linked to barcodes, may be compromised by unintended consequences of lentiviral packaging. Intermolecular recombination between library elements and integration of multiple perturbations (even at limiting virus dilution) can negatively impact the sensitivity of pooled screens. Here, we describe a simple approach to prevent recombination between lentiviral vectors containing multiple linked variable elements, such as the recently reported CRISP-seq, Perturb-seq, and Mosaic-seq designs. We show that modifying the packaging protocol by diluting the perturbation library with a carrier plasmid increases the fraction of correct, single integrations from <60% to >90%, at the cost of reducing titer by 100-fold.

genomics↗

Multiplexed enrichment and genomic profiling of peripheral immune cell subsets on a microfluidic chip

The human immune system consists of many specialized cell subsets that simultaneously carry out a diverse range of functions using overlapping pathways and signals. Subset-specific immune profiling can resolve immune activity in autoimmune disease, cancer immunity, and infectious disease that may not be discoverable or detectable in analyses of crude blood samples. The activity of specific subsets may help predict the course of disease and response to therapy in certain patient populations. Here, we present a low-input microfluidic system for sorting immune cells into subsets and profiling their cellular states by gene expression analysis using full-length RNA-seq. Our system is robust and has the potential to make multiplexed subset-specific analysis routine in many research laboratories and clinical settings. We validate the devices technical performance by benchmarking its subset enrichment and genomic profiling performance against standard protocols. We make the added value of subset-resolved profiling over crude samples clear through ex vivo experiments that show subset-specific stimulated responses. Finally, we demonstrate the scalability of our device by profiling four immune cell subsets in blood from systemic lupus erythematosus (SLE) patients and matched controls enrolled in a clinical study. The results from our initial cohort confirm the role of type I interferons in lupus pathogenesis and further show that the canonical interferon signature for SLE is prominent in B cells, demonstrating the ability of our integrated analytical platform to identify cell-specific disease signatures.

bioengineering↗

Combinatorial Drug Discovery in Nanoliter Droplets

Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here we report a high-throughput system for nanoliter-scale phenotypic screening that stabilizes a chemical library in nanoliter droplet emulsions and automates the formulation of chemical combinations en mass using parallel droplet processing. We apply this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against E. coli, a model Gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against Gram-positive bacteria but are not effective by themselves to resolve Gram-negative infections.

bioengineering↗

Targeting individual cells by barcode in pooled sequence libraries

There is rising interest in applying single-cell transcriptome analysis and other single-cell sequencing methods to resolve differences between cells. Pooled processing of thousands of single cells is now routinely practiced by introducing cell-specific DNA barcodes early in cell processing protocols1-5. However, researchers must sequence a large number of cells to sample rare subpopulations6-8, even when fluorescence-activated cell sorting (FACS) is used to pre-enrich rare cell populations. Here, a new molecular enrichment method is used in conjunction with FACS enrichment to enable efficient sampling of rare dendritic cell (DC) populations, including the recently identified AXL+SIGLEC6+ (AS DCs) subset7, within a 10X Genomics single-cell RNA-Seq library. DC populations collectively represent 1-2% of total peripheral blood mononuclear cells (PBMC), with AS DC representing only 1-3% of human blood DCs and 0.01-0.06% of total PBMCs.

bioengineering↗

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

Metagenomics and single-cell genomics have enabled the discovery of many new genomes from previously unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and in many respects represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes from complex samples. In addition, by generating 96 sub-samples from each environmental sample, this method maintains high throughput, reduces sample complexity, and preserves single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes larger than 0.5 Mbps. These genomes represent novel lineages at different taxonomic levels, including three deeply branching lineages. Functional analysis revealed that these organisms utilize diverse pathways for energy metabolism. The resolution of this mini-metagenomic method enabled accurate quantification of genome abundance, even for genomes less than 1% in relative abundance. Our analyses also revealed a wide range of genome level single nucleotide polymorphism (SNP) distributions with nonsynonymous to synonymous ratio indicative of low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomic make it a powerful tool to dissect the genomic structure microbial communities while effectively preserving the fundamental unit of biology, the single cell.

microbiology↗

Multiplexed confocal and super-resolution fluorescence imaging of cytoskeletal and neuronal synapse proteins

Neuronal synapses contain dozens of protein species whose expression levels and localizations are key determinants of synaptic transmission and plasticity. The spectral properties of fluorophores used in conventional microscopy limit the number of measured proteins to four species within a given sample. The ability to perform high-throughput confocal or super-resolution imaging of many proteins simultaneously without limitation in target number imposed by this spectral limit would enable large-scale characterization of synaptic protein networks in situ. Here, we introduce PRISM: Probe-based Imaging for Sequential Multiplexing, a method that sequentially utilizes either high affinity Locked Nucleic Acid (LNA) or low affinity DNA probes to enable diffraction-limited confocal and PAINT-based super-resolution imaging. High-affinity LNA probes offer high-throughput, confocal-based imaging compared with PAINT, which uses low affinity probes to realize localization-based super-resolution imaging. Simultaneous immunostaining of all targets is performed prior to imaging, followed by sequential LNA/DNA probe exchange that requires only minutes under mild wash conditions. We apply PRISM to quantify the co-expression levels and nanometer-scale organization of one dozen cytoskeletal and synaptic proteins within individual neuronal synapses. Our approach is scalable to dozens of target proteins and is compatible with high-content screening platforms commonly used to interrogate phenotypic changes associated with genetic and drug perturbations in a variety of cell types.

bioengineering↗