Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

This is a “Topic Page” article for PLOS Computational Biology.

     

Longitudinal Analysis of CCR5 and CXCR4 Usage in a Cohort of Antiretroviral Therapy-Na?ve Subjects with Progressive HIV-1 Subtype C Infection

HIV-1 subtype C (C-HIV) is responsible for most HIV-1 cases worldwide. Although the pathogenesis of C-HIV is thought to predominantly involve CCR5-restricted (R5) strains, we do not have a firm understanding of how frequently CXCR4-using (X4 and R5X4) variants emerge in subjects with progressive C-HIV infection. Nor do we completely understand the molecular determinants of coreceptor switching by C-HIV variants. Here, we characterized a panel of HIV-1 envelope glycoproteins (Envs) (n = 300) cloned sequentially from plasma of 21 antiretroviral therapy (ART)-naïve subjects who experienced progression from chronic to advanced stages of C-HIV infection, and show that CXCR4-using C-HIV variants emerged in only one individual. Mutagenesis studies and structural models suggest that the evolution of R5 to X4 variants in this subject principally involved acquisition of an “Ile-Gly” insertion in the gp120 V3 loop and replacement of the V3 “Gly-Pro-Gly” crown with a “Gly-Arg-Gly” motif, but that the accumulation of additional gp120 “scaffold” mutations was required for these V3 loop changes to confer functional effects. In this context, either of the V3 loop changes could confer possible transitional R5X4 phenotypes, but when present together they completely abolished CCR5 usage and conferred the X4 phenotype. Our results show that the emergence of CXCR4-using strains is rare in this cohort of untreated individuals with advanced C-HIV infection. In the subject where X4 variants did emerge, alterations in the gp120 V3 loop were necessary but not sufficient to confer CXCR4 usage.     

The influence of substrate type on macroinvertebrate assemblages within agricultural drainage ditches

Artificial drainage ditches are common features in lowland agricultural catchments that support a wide range of ecosystem services at the landscape scale. Current paradigms in river management suggest activities that increase habitat heterogeneity and complexity resulting in more diverse floral and faunal assemblages; however, it is not known if the same principles apply to artificial drainage ditch systems. We examined the effects of four artificial substrates, representing increasing habitat complexity and heterogeneity (bricks, gravel, netting and vegetation), on macroinvertebrate community structure within artificial drainage ditches. Each substrate type supported a distinct macroinvertebrate community highlighting the importance of habitat heterogeneity in maintaining macroinvertebrate assemblages. Each substrate type also displayed differing degrees of community heterogeneity, with gravel communities being most variable and artificial vegetation being the least. In addition, several macroinvertebrate diversity metrics increased along the gradient of artificial substrate complexity, although these differences were not statistically significant. We conclude that habitat management practices that increase habitat complexity are likely to enhance macroinvertebrate community heterogeneity within artificial drainage channels regardless of previous management activities.

     

Bioreactor studies predict whole microbial population dynamics in oil sands tailings ponds

Microorganisms in oil sands fluid fine tailings (FFT) are critical to biogeochemical elemental cycling as well as to the degradation of residual hydrocarbon constituents and subsequent methane and CO₂ production. Microbial activity enhances particulate matter sedimentation rates and the dewatering of FFT materials, allowing water to be recycled back into bitumen extraction. A bulk of this evidence comes from bioreactor studies and has implications for engineering and environmental management of the FFT ponds. Yet, it is largely uncertain whether such laboratory populations are representative of whole field scale microbial communities. By using population ecology tools, we compared whole microbial communities present in FFT bioreactors to reference populations existing in Syncrude's West In Pit (WIP) tailings pond. Bacteria were found to be persistent in a sulfidic zone in both the oxic and anoxic bioreactors at all occasions tested. In contrast to the WIP, archaea only became predominant in bioreactors after 300 days, at which point analysis of similarity (global R statistic p?<?0.5) revealed no significant dissimilarities between the populations present in either system. A whole community succession pattern from bacterial dominated prevalence to a new assemblage predominated by archaea was suggested. These results have implications for the stepwise development of microbial model systems for predictive management of field scale FFT basins.     

Multi‐scale spatial heterogeneity of pectic rhamnogalacturonan I (RG–I) structural features in tobacco seed endosperm cell walls

Plant cell walls are complex configurations of polysaccharides that fulfil a diversity of roles during plant growth and development. They also provide sets of biomaterials that are widely exploited in food, fibre and fuel applications. The pectic polysaccharides, which comprise approximately a third of primary cell walls, form complex supramolecular structures with distinct glycan domains. Rhamnogalacturonan I (RG–I) is a highly structurally heterogeneous branched glycan domain within the pectic supramolecule that contains rhamnogalacturonan, arabinan and galactan as structural elements. Heterogeneous RG–I polymers are implicated in generating the mechanical properties of cell walls during cell development and plant growth, but are poorly understood in architectural, biochemical and functional terms. Using specific monoclonal antibodies to the three major RG–I structural elements (arabinan, galactan and the rhamnogalacturonan backbone) for in situ analyses and chromatographic detection analyses, the relative occurrences of RG–I structures were studied within a single tissue: the tobacco seed endosperm. The analyses indicate that the features of the RG–I polymer display spatial heterogeneity at the level of the tissue and the level of single cell walls, and also heterogeneity at the biochemical level. This work has implications for understanding RG–I glycan complexity in the context of cell‐wall architectures and in relation to cell‐wall functions in cell and tissue development.     

Extreme drought pushes stream invertebrate communities over functional thresholds

Functional traits are increasingly being used to predict extinction risks and range shifts under long‐term climate change scenarios, but have rarely been used to study vulnerability to extreme climatic events, such as supraseasonal droughts. In streams, drought intensification can cross thresholds of habitat loss, where marginal changes in environmental conditions trigger disproportionate biotic responses. However, these thresholds have been studied only from a structural perspective, and the existence of functional nonlinearity remains unknown. We explored trends in invertebrate community functional traits along a gradient of drought intensity, simulated over 18 months, using mesocosms analogous to lowland headwater streams. We modelled the responses of 16 traits based on a priori predictions of trait filtering by drought, and also examined the responses of trait profile groups (TPGs) identified via hierarchical cluster analysis. As responses to drought intensification were both linear and nonlinear, generalized additive models (GAMs) were chosen to model response curves, with the slopes of fitted splines used to detect functional thresholds during drought. Drought triggered significant responses in 12 (75%) of the a priori‐selected traits. Behavioural traits describing movement (dispersal, locomotion) and diet were sensitive to moderate‐intensity drought, as channels fragmented into isolated pools. By comparison, morphological and physiological traits showed little response until surface water was lost, at which point we observed sudden shifts in body size, respiration mode and thermal tolerance. Responses varied widely among TPGs, ranging from population collapses of non‐aerial dispersers as channels fragmented to irruptions of small, eurythermic dietary generalists upon extreme dewatering. Our study demonstrates for the first time that relatively small changes in drought intensity can trigger disproportionately large functional shifts in stream communities, suggesting that traits‐based approaches could be particularly useful for diagnosing catastrophic ecological responses to global change.     

Prospects for seascape repair: Three case studies from eastern Australia

Three case studies spanning tropical, subtropical and temperate environments highlight the minimum potential benefits of investing in repair of coastal seascapes. Fisheries, a market benefit indicator readily understood by a range of stakeholders from policymakers to community advocates, were used as a surrogate for ecosystem services generated through seascape habitat restoration. For each case study, while recognising that biological information will always remain imperfect, the prospects for seascape repair are compelling.     

Single-Cell Sequencing of iPSC-Dopamine Neurons Reconstructs Disease Progression and Identifies HDAC4 as a Regulator of Parkinson Cell Phenotypes

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