A stagewise response to mitochondrial dysfunction in mitochondrial DNA maintenance disorders.

Mitochondrial DNA (mtDNA) deletions which clonally expand in skeletal muscle of patients with mtDNA maintenance disorders, impair mitochondrial oxidative phosphorylation dysfunction. Previously we have shown that these mtDNA deletions arise and accumulate in perinuclear mitochondria causing localised mitochondrial dysfunction before spreading through the muscle fibre. We believe that mito-nuclear signalling is a key contributor in the accumulation and spread of mtDNA deletions, and that knowledge of how muscle fibres respond to mitochondrial dysfunction is key to our understanding of disease mechanisms. To understand the contribution of mito-nuclear signalling to the spread of mitochondrial dysfunction, we use imaging mass cytometry. We characterise the levels of mitochondrial Oxidative Phosphorylation proteins alongside a mitochondrial mass marker, in a cohort of patients with mtDNA maintenance disorders. Our expanded panel included protein markers of key signalling pathways, allowing us to investigate cellular responses to different combinations of oxidative phosphorylation dysfunction and ragged red fibres. We find combined Complex I and IV deficiency to be most common. Interestingly, in fibres deficient for one or more complexes, the remaining complexes are often upregulated beyond the increase of mitochondrial mass typically observed in ragged red fibres. We further find that oxidative phosphorylation deficient fibres exhibit an increase in the abundance of proteins involved in proteostasis, e.g. HSP60 and LONP1, and regulation of mitochondrial metabolism (including oxidative phosphorylation and proteolysis, e.g. PHB1). Our analysis suggests that the cellular response to mitochondrial dysfunction changes depending on the combination of deficient oxidative phosphorylation complexes in each fibre.

Single-cell insights into immune dysregulation in rheumatoid arthritis flare versus drug-free remission.

Immune-mediated inflammatory diseases (IMIDs) are typically characterised by relapsing and remitting flares of inflammation. However, the unpredictability of disease flares impedes their study. Addressing this critical knowledge gap, we use the experimental medicine approach of immunomodulatory drug withdrawal in rheumatoid arthritis (RA) remission to synchronise flare processes allowing detailed characterisation. Exploratory mass cytometry analyses reveal three circulating cellular subsets heralding the onset of arthritis flare - CD45RO+PD1hi CD4+ and CD8+ T cells, and CD27+CD86+CD21- B cells - further characterised by single-cell sequencing. Distinct lymphocyte subsets including cytotoxic and exhausted CD4+ memory T cells, memory CD8+CXCR5+ T cells, and IGHA1+ plasma cells are primed for activation in flare patients. Regulatory memory CD4+ T cells (Treg cells) increase at flare onset, but with dysfunctional regulatory marker expression compared to drug-free remission. Significant clonal expansion is observed in T cells, but not B cells, after drug cessation; this is widespread throughout memory CD8+ T cell subsets but limited to the granzyme-expressing cytotoxic subset within CD4+ memory T cells. Based on our observations, we suggest a model of immune dysregulation for understanding RA flare, with potential for further translational research towards novel avenues for its treatment and prevention.

Imaging mass cytometry analysis of Becker muscular dystrophy muscle samples reveals different stages of muscle degeneration.

Becker muscular dystrophy (BMD) is characterised by fiber loss and expansion of fibrotic and adipose tissue. Several cells interact locally in what is known as the degenerative niche. We analysed muscle biopsies of controls and BMD patients at early, moderate and advanced stages of progression using Hyperion imaging mass cytometry (IMC) by labelling single sections with 17 markers identifying different components of the muscle. We developed a software for analysing IMC images and studied changes in the muscle composition and spatial correlations between markers across disease progression. We found a strong correlation between collagen-I and the area of stroma, collagen-VI, adipose tissue, and M2-macrophages number. There was a negative correlation between the area of collagen-I and the number of satellite cells (SCs), fibres and blood vessels. The comparison between fibrotic and non-fibrotic areas allowed to study the disease process in detail. We found structural differences among non-fibrotic areas from control and patients, being these latter characterized by increase in CTGF and in M2-macrophages and decrease in fibers and blood vessels. IMC enables to study of changes in tissue structure along disease progression, spatio-temporal correlations and opening the door to better understand new potential pathogenic pathways in human samples.

Guidelines for establishing a cytometry laboratory.

The purpose of this document is to provide guidance for establishing and maintaining growth and development of flow cytometry shared resource laboratories. While the best practices offered in this manuscript are not intended to be universal or exhaustive, they do outline key goals that should be prioritized to achieve operational excellence and meet the needs of the scientific community. Additionally, this document provides information on available technologies and software relevant to shared resource laboratories. This manuscript builds on the work of Barsky et al. 2016 published in Cytometry Part A and incorporates recent advancements in cytometric technology. A flow cytometer is a specialized piece of technology that require special care and consideration in its housing and operations. As with any scientific equipment, a thorough evaluation of the location, space requirements, auxiliary resources, and support is crucial for successful operation. This comprehensive resource has been written by past and present members of the International Society for Advancement of Cytometry (ISAC) Shared Resource Laboratory (SRL) Emerging Leaders Program https://isac-net.org/general/custom.asp?page=SRL-Emerging-Leaders with extensive expertise in managing flow cytometry SRLs from around the world in different settings including academia and industry. It is intended to assist in establishing a new flow cytometry SRL, re-purposing an existing space into such a facility, or adding a flow cytometer to an individual lab in academia or industry. This resource reviews the available cytometry technologies, the operational requirements, and best practices in SRL staffing and management.

OPTIMAL: An OPTimized Imaging Mass cytometry AnaLysis framework for benchmarking segmentation and data exploration.

Analysis of imaging mass cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single-cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single-cell suspension technologies. To this end we have developed the "OPTimized Imaging Mass cytometry AnaLysis (OPTIMAL)" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization/clustering, and spatial neighborhood analysis. Using a panel of 27 metal-tagged antibodies recognizing well-characterized phenotypic and functional markers to stain the same Formalin-Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single-cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bivariate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple Z-score normalization step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single-cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.

Distinct lung cell signatures define the temporal evolution of diffuse alveolar damage in fatal COVID-19.

BACKGROUND: Lung damage in severe COVID-19 is highly heterogeneous however studies with dedicated spatial distinction of discrete temporal phases of diffuse alveolar damage (DAD) and alternate lung injury patterns are lacking. Existing studies have also not accounted for progressive airspace obliteration in cellularity estimates. We used an imaging mass cytometry (IMC) analysis with an airspace correction step to more accurately identify the cellular immune response that underpins the heterogeneity of severe COVID-19 lung disease. METHODS: Lung tissue was obtained at post-mortem from severe COVID-19 deaths. Pathologist-selected regions of interest (ROIs) were chosen by light microscopy representing the patho-evolutionary spectrum of DAD and alternate disease phenotypes were selected for comparison. Architecturally normal SARS-CoV-2-positive lung tissue and tissue from SARS-CoV-2-negative donors served as controls. ROIs were stained for 40 cellular protein markers and ablated using IMC before segmented cells were classified. Cell populations corrected by ROI airspace and their spatial relationships were compared across lung injury patterns. FINDINGS: Forty patients (32M:8F, age: 22-98), 345 ROIs and >900k single cells were analysed. DAD progression was marked by airspace obliteration and significant increases in mononuclear phagocytes (MnPs), T and B lymphocytes and significant decreases in alveolar epithelial and endothelial cells. Neutrophil populations proved stable overall although several interferon-responding subsets demonstrated expansion. Spatial analysis revealed immune cell interactions occur prior to microscopically appreciable tissue injury. INTERPRETATION: The immunopathogenesis of severe DAD in COVID-19 lung disease is characterised by sustained increases in MnPs and lymphocytes with key interactions occurring even prior to lung injury is established. FUNDING: UK Research and Innovation/Medical Research Council through the UK Coronavirus Immunology Consortium, Barbour Foundation, General Sir John Monash Foundation, Newcastle University, JGW Patterson Foundation, Wellcome Trust.

Parkinson's disease neurons exhibit alterations in mitochondrial quality control proteins.

Mitochondrial dysfunction has been suggested to contribute to Parkinson's disease pathogenesis, though an understanding of the extent or exact mechanism of this contribution remains elusive. This has been complicated by challenging nature of pathway-based analysis and an inability simultaneously study multiple related proteins within human brain tissue. We used imaging mass cytometry (IMC) to overcome these challenges, measuring multiple protein targets, whilst retaining the spatial relationship between targets in post-mortem midbrain sections. We used IMC to simultaneously interrogate subunits of the mitochondrial oxidative phosphorylation complexes, and several key signalling pathways important for mitochondrial homoeostasis, in a large cohort of PD patient and control cases. We revealed a generalised and synergistic reduction in mitochondrial quality control proteins in dopaminergic neurons from Parkinson's patients. Further, protein-protein abundance relationships appeared significantly different between PD and disease control tissue. Our data showed a significant reduction in the abundance of PINK1, Parkin and phosphorylated ubiquitinSer65, integral to the mitophagy machinery; two mitochondrial chaperones, HSP60 and PHB1; and regulators of mitochondrial protein synthesis and the unfolded protein response, SIRT3 and TFAM. Further, SIRT3 and PINK1 did not show an adaptive response to an ATP synthase defect in the Parkinson's neurons. We also observed intraneuronal aggregates of phosphorylated ubiquitinSer65, alongside increased abundance of mitochondrial proteases, LONP1 and HTRA2, within the Parkinson's neurons with Lewy body pathology, compared to those without. Taken together, these findings suggest an inability to turnover mitochondria and maintain mitochondrial proteostasis in Parkinson's neurons. This may exacerbate the impact of oxidative phosphorylation defects and ageing related oxidative stress, leading to neuronal degeneration. Our data also suggest that that Lewy pathology may affect mitochondrial quality control regulation through the disturbance of mitophagy and intramitochondrial proteostasis.

Tissue factor expression in monocyte subsets during human immunothrombosis, endotoxemia and sepsis.

INTRODUCTION: Tissue factor expression on monocytes is implicated in the pathophysiology of sepsis-induced coagulopathy. How tissue factor is expressed by monocyte subsets (classical, intermediate and non-classical) is unknown. METHODS: Monocytic tissue factor surface expression was investigated during three conditions. Primary human monocytes and microvascular endothelial cell co-cultures were used for in vitro studies. Volunteers received a bolus of lipopolysaccharide (2 ng/kg) to induce endotoxemia. Patients with sepsis, or controls with critical illness unrelated to sepsis, were recruited from four intensive care units. RESULTS: Contact with endothelium and stimulation with lipopolysaccharide reduced the proportion of intermediate monocytes. Lipopolysaccharide increased tissue factor surface expression on classical and non-classical monocytes. Endotoxemia induced profound, transient monocytopenia, along with activation of coagulation pathways. In the remaining circulating monocytes, tissue factor was up-regulated in intermediate monocytes, though approximately 60 % of individuals (responders) up-regulated tissue factor across all monocyte subsets. In critically ill patients, tissue factor expression on intermediate and non-classical monocytes was significantly higher in patients with established sepsis than among non-septic patients. Upon recovery of sepsis, expression of tissue factor increased significantly in classical monocytes. CONCLUSION: Tissue factor expression in monocyte subsets varies significantly during health, endotoxemia and sepsis.

Programmed cell death-1 receptor-mediated regulation of Tbet+NK1.1- innate lymphoid cells within the tumor microenvironment.

Innate lymphoid cells (ILCs) play a key role in tissue-mediated immunity and can be controlled by coreceptor signaling. Here, we define a subset of ILCs that are Tbet+NK1.1- and are present within the tumor microenvironment (TME). We show programmed death-1 receptor (PD-1) expression on ILCs within TME is found in Tbet+NK1.1- ILCs. PD-1 significantly controlled the proliferation and function of Tbet+NK1.1- ILCs in multiple murine and human tumors. We found tumor-derived lactate enhanced PD-1 expression on Tbet+NK1.1- ILCs within the TME, which resulted in dampened the mammalian target of rapamycin (mTOR) signaling along with increased fatty acid uptake. In line with these metabolic changes, PD-1-deficient Tbet+NK1.1- ILCs expressed significantly increased IFNγ and granzyme B and K. Furthermore, PD-1-deficient Tbet+NK1.1- ILCs contributed toward diminished tumor growth in an experimental murine model of melanoma. These data demonstrate that PD-1 can regulate antitumor responses of Tbet+NK1.1- ILCs within the TME.

Identification of a protein expression signature distinguishing early from organising diffuse alveolar damage in COVID-19 patients.

Diffuse alveolar damage (DAD) is the histological expression of acute respiratory distress syndrome and characterises lung pathology due to infection with SARS-CoV-2, and other respiratory pathogens of clinical significance. DAD reflects a time-dependent immunopathological process, progressing from an early/exudative stage through to an organising/fibrotic stage, yet within an individual these different stages of DAD may coexist. Understanding the progression of DAD is central to the development of new therapeutics to limit progressive lung damage. Here, we applied highly multiplexed spatial protein profiling to autopsy lung tissues derived from 27 patients who died from COVID-19 and identified a protein signature (ARG1, CD127, GZMB, IDO1, Ki67, phospho-PRAS40 (T246) and VISTA) that distinguishes early DAD from late DAD with good predictive accuracy. These proteins warrant further investigation as potential regulators of DAD progression.

Downregulation of MALAT1 is a hallmark of tissue and peripheral proliferative T cells in COVID-19.

T cells play key protective but also pathogenic roles in COVID-19. We studied the expression of long non-coding RNAs (lncRNAs) in COVID-19 T-cell transcriptomes by integrating previously published single-cell RNA sequencing datasets. The long intergenic non-coding RNA MALAT1 was the most highly transcribed lncRNA in T cells, with Th1 cells demonstrating the lowest and CD8+ resident memory cells the highest MALAT1 expression, amongst CD4+ and CD8+ T-cells populations, respectively. We then identified gene signatures that covaried with MALAT1 in single T cells. A significantly higher number of transcripts correlated negatively with MALAT1 than those that correlated. Enriched functional annotations of the MALAT1- anti-correlating gene signature included processes associated with T-cell activation such as cell division, oxidative phosphorylation, and response to cytokine. The MALAT1 anti-correlating gene signature shared by both CD4+ and CD8+ T-cells marked dividing T cells in both the lung and blood of COVID-19 patients. Focussing on the tissue, we used an independent patient cohort of post-mortem COVID-19 lung samples and demonstrated that MALAT1 suppression was indeed a marker of MKI67+ proliferating CD8+ T cells. Our results reveal MALAT1 suppression and its associated gene signature are a hallmark of human proliferating T cells.

GBMdeconvoluteR accurately infers proportions of neoplastic and immune cell populations from bulk glioblastoma transcriptomics data.

BACKGROUND: Characterizing and quantifying cell types within glioblastoma (GBM) tumors at scale will facilitate a better understanding of the association between the cellular landscape and tumor phenotypes or clinical correlates. We aimed to develop a tool that deconvolutes immune and neoplastic cells within the GBM tumor microenvironment from bulk RNA sequencing data. METHODS: We developed an IDH wild-type (IDHwt) GBM-specific single immune cell reference consisting of B cells, T-cells, NK-cells, microglia, tumor associated macrophages, monocytes, mast and DC cells. We used this alongside an existing neoplastic single cell-type reference for astrocyte-like, oligodendrocyte- and neuronal progenitor-like and mesenchymal GBM cancer cells to create both marker and gene signature matrix-based deconvolution tools. We applied single-cell resolution imaging mass cytometry (IMC) to ten IDHwt GBM samples, five paired primary and recurrent tumors, to determine which deconvolution approach performed best. RESULTS: Marker-based deconvolution using GBM-tissue specific markers was most accurate for both immune cells and cancer cells, so we packaged this approach as GBMdeconvoluteR. We applied GBMdeconvoluteR to bulk GBM RNAseq data from The Cancer Genome Atlas and recapitulated recent findings from multi-omics single cell studies with regards associations between mesenchymal GBM cancer cells and both lymphoid and myeloid cells. Furthermore, we expanded upon this to show that these associations are stronger in patients with worse prognosis. CONCLUSIONS: GBMdeconvoluteR accurately quantifies immune and neoplastic cell proportions in IDHwt GBM bulk RNA sequencing data and is accessible here: https://gbmdeconvoluter.leeds.ac.uk.

Hyperactive CREB subpopulations increase during therapy in pediatric B-lineage acute lymphoblastic leukemia.

Persistence of residual disease in acute lymphoblastic leukemia (ALL) during the initial stages of chemotherapy is associated with inferior survival. To better understand clonal evolution and mechanisms of chemoresistance, we used multiparameter mass cytometry, at single-cell resolution, to functionally characterize pediatric B-ALL cells at disease presentation and those persisting during induction therapy. Analysis of ALL cells from presentation samples (n=42) showed that the most abundant phosphosignals were pCREB, pH2AX and pHH3 and we identified JAK-STAT and RAS pathway activation in five of six patients with JAK or RAS genetic aberrations. The clonal composition of ALL was heterogeneous and dynamic during treatment but all viable cell clusters showed pCREB activation. Levels of pCREB in ALL cells were increased or maintained during therapy and high dimensional analysis revealed a subpopulation of ALL cells at presentation that was positive for pCREB/pHH3/pS6 which increased during treatment in some patients, implicating this signaling node in conferring a survival advantage to multi-agent induction therapy. The small molecule CREB inhibitor, 666-15, was shown to reduce CREB transcriptional activity and induce apoptosis in ALL patient-derived xenograft cells of varying cytogenetic subtypes in vitro, both in the presence and absence of stromal support. Together, these data suggest that the cAMP signaling pathway may provide an opportunity for minimal residual disease-directed therapy for many patients at high risk of relapse.

The trajectory of COVID-19 cardiopulmonary disease: insights from an autopsy study of community-based, pre-hospital deaths.

Background: Post mortem examination of lung and heart tissue has been vital to developing an understanding of COVID-19 pathophysiology; however studies to date have almost uniformly used tissue obtained from hospital-based deaths where individuals have been exposed to major medical and pharmacological interventions. Methods: In this study we investigated patterns of lung and heart injury from 46 community-based, pre-hospital COVID-19-attributable deaths who underwent autopsy. Results: The cohort comprised 22 females and 24 males, median age 64 years (range 19-91) at time of death with illness duration range 0-23 days. Comorbidities associated with poor outcomes in COVID-19 included obesity (body mass index >30 kg·m-2) in 19 out of 46 cases (41.3%). Diffuse alveolar damage in its early exudative phase was the most common pattern of lung injury; however significant heterogeneity was identified with bronchopneumonia, pulmonary oedema consistent with acute cardiac failure, pulmonary thromboembolism and microthrombosis also identified and often in overlapping patterns. Review of clinical records and next of kin accounts suggested a combination of unexpectedly low symptom burden, rapidly progressive disease and psychosocial factors may have contributed to a failure of hospital presentation prior to death. Conclusions: Identifying such advanced acute lung injury in community-based deaths is extremely unusual and raises the question why some with severe COVID-19 pneumonitis were not hospitalised. Multiple factors including low symptom burden, rapidly progressive disease trajectories and psychosocial factors provide possible explanations.

Immune processes in the pathogenesis of chronic lung allograft dysfunction: identifying the missing pieces of the puzzle.

Lung transplantation is the optimal treatment for selected patients with end-stage chronic lung diseases. However, chronic lung allograft dysfunction remains the leading obstacle to improved long-term outcomes. Traditionally, lung allograft rejection has been considered primarily as a manifestation of cellular immune responses. However, in reality, an array of complex, interacting and multifactorial mechanisms contribute to its emergence. Alloimmune-dependent mechanisms, including T-cell-mediated rejection and antibody-mediated rejection, as well as non-alloimmune injuries, have been implicated. Moreover, a role has emerged for autoimmune responses to lung self-antigens in the development of chronic graft injury. The aim of this review is to summarise the immune processes involved in the pathogenesis of chronic lung allograft dysfunction, with advanced insights into the role of innate immune pathways and crosstalk between innate and adaptive immunity, and to identify gaps in current knowledge.

CXCR2 inhibition enables NASH-HCC immunotherapy.

OBJECTIVE: Hepatocellular carcinoma (HCC) is increasingly associated with non-alcoholic steatohepatitis (NASH). HCC immunotherapy offers great promise; however, recent data suggests NASH-HCC may be less sensitive to conventional immune checkpoint inhibition (ICI). We hypothesised that targeting neutrophils using a CXCR2 small molecule inhibitor may sensitise NASH-HCC to ICI therapy. DESIGN: Neutrophil infiltration was characterised in human HCC and mouse models of HCC. Late-stage intervention with anti-PD1 and/or a CXCR2 inhibitor was performed in murine models of NASH-HCC. The tumour immune microenvironment was characterised by imaging mass cytometry, RNA-seq and flow cytometry. RESULTS: Neutrophils expressing CXCR2, a receptor crucial to neutrophil recruitment in acute-injury, are highly represented in human NASH-HCC. In models of NASH-HCC lacking response to ICI, the combination of a CXCR2 antagonist with anti-PD1 suppressed tumour burden and extended survival. Combination therapy increased intratumoural XCR1+ dendritic cell activation and CD8+ T cell numbers which are associated with anti-tumoural immunity, this was confirmed by loss of therapeutic effect on genetic impairment of myeloid cell recruitment, neutralisation of the XCR1-ligand XCL1 or depletion of CD8+ T cells. Therapeutic benefit was accompanied by an unexpected increase in tumour-associated neutrophils (TANs) which switched from a protumour to anti-tumour progenitor-like neutrophil phenotype. Reprogrammed TANs were found in direct contact with CD8+ T cells in clusters that were enriched for the cytotoxic anti-tumoural protease granzyme B. Neutrophil reprogramming was not observed in the circulation indicative of the combination therapy selectively influencing TANs. CONCLUSION: CXCR2-inhibition induces reprogramming of the tumour immune microenvironment that promotes ICI in NASH-HCC.

Detecting respiratory chain defects in osteoblasts from osteoarthritic patients using imaging mass cytometry.

Osteoporosis is a skeletal disease which is characterised by reduced bone mass and microarchitecture, with a subsequent loss of strength that predisposes to fragility and risk of fractures. The pathogenesis of falling bone mineral density, ultimately leading to a diagnosis of osteoporosis is incompletely understood but the disease is currently thought to be multifactorial. Humans are known to accumulate mitochondrial mutations and respiratory chain deficiency with age and mounting evidence suggests that this may indeed be the overarching cause intrinsic to the changing phenotype in advancing age and age-related disease. Mitochondrial mutations are detectable from the age of about 30 years onwards. Mitochondria contain their own genome which encodes 13 essential mitochondrial proteins and accumulates somatic variants at up to 10 times the rate of the nuclear genome. Once the concentration of any pathogenic mitochondrial genome variant exceeds a threshold, respiratory chain deficiency and cellular dysfunction occur. The PolgD257A/D257A mouse model is a knock-in mutant that expresses a proof-reading-deficient version of PolgA, a nuclear encoded subunit of mtDNA polymerase. These mice are a useful model of age-related accumulation of mtDNA mutations in humans since their defective proof-reading mechanism leads to a mitochondrial DNA mutation rate 3-5 times higher than in wild-type mice. These mice showed enhanced levels of age-related osteoporosis along with respiratory chain deficiency in osteoblasts. To explore whether respiratory chain deficiency is also seen in human osteoblasts, we developed a protocol and analysis framework for imaging mass cytometry in bone tissue sections to analyse osteoblasts in situ. By comparing bone tissue sampled at one timepoint from femoral neck of 10 older healthy volunteers aged 40-85 with samples from young patients aged 1-19, we have identified complex I defect in osteoblasts from 6 out of 10 older volunteers, complex II defect in 2 out of 10 older volunteers, complex IV defect in 1 out of 10 older volunteers and complex V defect in 4 out of 10 older volunteers. These observations are consistent with findings from the PolgD257A/D257A mouse model and suggest that respiratory chain deficiency, as a consequence of the accumulation of age-related pathogenic mitochondrial DNA mutations, may play a significant role in the pathogenesis of human age-related osteoporosis.

Effector immune cells in chronic lung allograft dysfunction: A systematic review.

Chronic lung allograft dysfunction (CLAD) remains the major barrier to long-term survival after lung transplantation and improved insight into its underlying immunological mechanisms is critical to better understand the disease and to identify treatment targets. We systematically searched the electronic databases of PubMed and EMBASE for original research publications, published between January 2000 and April 2021, to comprehensively assess current evidence on effector immune cells in lung tissue and bronchoalveolar lavage fluid from lung transplant recipients with CLAD. Literature search revealed 1351 articles, 76 of which met the criteria for inclusion in our analysis. Our results illustrate significant complexity in both innate and adaptive immune cell responses in CLAD, along with presence of numerous immune cell products, including cytokines, chemokines and proteases associated with tissue remodelling. A clear link between neutrophils and eosinophils and CLAD incidence has been seen, in which eosinophils more specifically predisposed to restrictive allograft syndrome. The presence of cytotoxic and T-helper cells in CLAD pathogenesis is well-documented, although it is challenging to draw conclusions about their role in tissue processes from predominantly bronchoalveolar lavage data. In restrictive allograft syndrome, a more prominent humoral immune involvement with increased B cells, immunoglobulins and complement deposition is seen. Our evaluation of published studies over the last 20 years summarizes the complex multifactorial immunopathology of CLAD onset and progression. It highlights the phenotype of several key effector immune cells involved in CLAD pathogenesis, as well as the paucity of single cell resolution spatial studies in lung tissue from patients with CLAD.

Imaging flow cytometry: a primer.

Imaging flow cytometry combines the high throughput nature of flow cytometry with the advantages of single cell image acquisition associated with microscopy. The measurement of large numbers of features from the resulting images provides rich datasets which have resulted in a wide range of novel biomedical applications. In this primer we discuss the typical imaging flow instrumentation, the form of data acquired and the typical analysis tools that can be applied to this data. Using examples from the literature we discuss the progression of the analysis methods that have been applied to imaging flow cytometry data. These methods start from the use of simple single image features and multiple channel gating strategies, followed by the design and use of custom features for phenotype classification, through to powerful machine and deep learning methods. For each of these methods, we outline the processes involved in analyzing typical datasets and provide details of example applications. Finally we discuss the current limitations of imaging flow cytometry and the innovations which are addressing these challenges.