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Biology subjects

Digman, M.

Publications and source records attributed to Digman, M..

8 recordsLinked to original sources

Unleashed condensation by recurrent mutations of an epigenetic regulator promotes cancer

The pathological mechanisms and significance for the prevalent hotspot mutations in disordered protein regions are poorly understood. ASXL1 is an obligate co-factor for BAP1 in H2AK119 deubiquitination. ASXL1 mutations are very frequent in myeloid malignancies, and are mostly C-terminal truncating mutations concentrated in a specific disordered region of ASXL1. ASXL1 truncations are gain-of-function mutations that promote myeloid malignancies, but the underlying mechanisms remain poorly understood. Here we show that the frequently truncated mutants of ASXL1 possess an intrinsic property of forming phase-separated biomolecular condensates, and this property is normally suppressed by the frequently deleted regions. A disease-mutant of the endogenous ASXL1 in leukemia cells forms dynamic nuclear co-condensates with other endogenous factors important for gene activation. The ASXL1 disease-mutants can greatly enhance H2A deubiquitination activity of BAP1 in cells and in vitro reconstituted system, enhance myeloid leukemia cell growth, and promote leukemogenesis in a mouse transplant model by turning on myeloid leukemogenic transcriptional programs. However, substitution of residues important for condensation disrupted or impaired all these abilities, suggesting that the condensation property is crucially important for the ASXL1 mutants in promoting cancer. Moreover, we discover that the conserved negative charges in the highly disordered and frequently deleted region on ASXL1 suppress the condensation of the wild type ASXL1. Charge-neutralizing mutations in this region restores condensation of the full-length ASXL1, and are sufficient to turn ASXL1 into a leukemogenic protein. Biochemical, biophysical, and simulation analyses suggest the intramolecular interactions normally mask the N-terminal region in engaging intermolecular interactions required for phase separation, and disease truncations escape from the regulatory interactions and unleash the phase separation property to form nuclear hubs to promote expression of tumorigenic gene programs. Finally, by showing a striking correlation of the mutation frequencies with the condensation properties and leukemogenesis activity for a series of human patient mutations, we suggest that dysregulation of condensation is a central mechanism for ASXL1 mutations in promoting myeloid malignancies. This suggests that dysregulation of condensation may be a key mechanism for some of the prevalent hotspot disease mutations in the disordered proteomes.

biochemistry↗

Highly multiplexed spectral FLIM via physics informed data analysis

Spectral fluorescence lifetime imaging (S-FLIM) allows for the simultaneous deconvolution of signal from multiple fluorophore species by leveraging both spectral and lifetime information. However, existing analyses still face multiple difficulties in decoding information collected from typical S-FLIM experiments. These include: using information from pre-calibrated spectra in environments that may differ from the cellular context in which S-FLIM experiments are performed; limitations in the ability to deconvolute species due to overlapping spectra; high photon budget requirements, typically about a hundred photons per pixel per species. Yet information on the spectra themselves are already encoded in the data and do not require pre-calibration. What is more, efficient photon-by-photon analyses are possible reducing both the required photon budget and making it possible to use larger budgets in order to discriminate small differences in spectra to resolve spatially co-localized fluorophore species. To achieve this, we propose a Bayesian S-FLIM framework capable of simultaneously learning spectra and lifetimes photon-by-photon ultimately using limited photon counts and being highly data efficient. We demonstrate the proposed framework using a range of synthetic and experimental data and show that it can deconvolve up to 9 species with heavily overlapped spectra.

biophysics↗

ESPRESSO: Spatiotemporal omics based on organelle phenotyping

Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have been instrumental to improving our understanding of complex biological systems. Despite fast-pace advancements, a crucial dimension is still left to explore: time. To capture this key parameter, we introduce ESPRESSO (Environmental Sensor Phenotyping RElayed by Subcellular Structures and Organelles), a pioneering technique that provides high-dimensional phenotyping resolved in space and time. Through a novel paradigm, ESPRESSO combines fluorescent labeling, advanced microscopy and bioimage and data analysis to extract morphological and functional information of the organelle network unveiling phenotypic changes over time at the single-cell level. In this work, we present ESPRESSOs methodology and its application across numerous cellular systems, showcasing its ability to discern cell types, stress response, differentiation and immune cells polarization. We then correlate ESPRESSO phenotypic changes with gene expression and demonstrate its applicability to 3D cultures, offering a path to revolutionizing biological exploration, providing invaluable insights into cellular states in both space and time.

bioengineering↗

The microenvironment dictates glycocalyx construction and immune surveillance

Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with in vitro models that do not match the microenvironmental characteristics of human tissues. Using in vitro models which mimic the physical properties of healthy or cancerous tissues and a physiologically relevant culture medium, we demonstrate that the chemical and physical properties of the microenvironment regulate the composition and topology of the glycocalyx. Remarkably, we find that cancer and age-related changes in the physical properties of the microenvironment are sufficient to adjust immune surveillance via the topology of the glycocalyx, a previously unknown phenomenon observable only with a physiologically relevant culture medium. Key PointsO_LICulture medium dictates cellular mechanoresponse signatures in vitro C_LIO_LIEpithelial glycocalyx construction is mediated by Heat Shock Factor 1 (HSF1) C_LIO_LISialic acid topology dictates Natural Killer cell cytotoxicity C_LIO_LIPhysiological microenvironments reveal distinct glycobiology C_LI

cell biology↗

Building Fluorescence Lifetime Maps Photon-by-photon by Leveraging Spatial Correlations

Fluorescence lifetime imaging microscopy (FLIM) has become a standard tool in the quantitative analysis of sub-cellular environments. However, quantitative FLIM analyses face several challenges. First, spatial correlations between pixels are often ignored as signal from individual pixels is analyzed independently thereby limiting spatial resolution. Second, existing methods deduce photon ratios instead of absolute lifetime maps. Next, the number of lifetime components contributing to the signal is unknown, while excited state lifetimes with <1 ns difference are difficult to discriminate. Finally, existing analyses require high photon budgets, and often cannot rigorously propagate experimental uncertainty into values over lifetime maps and number of components involved. To overcome all of these challenges simultaneously and self-consistently at once, we propose the first doubly nonparametric framework. That is, we learn the number of fluorescent species (through beta-Bernoulli process priors) and absolute lifetime maps of these species (through Gaussian process priors) by leveraging information from pulses not leading to observed photon. We benchmark our algorithm using a broad range of synthetic and experimental data and demonstrate its robustness across a number of scenarios including cases where we recover lifetime differences between components as small as 0.3 ns with merely 1000 photons.

biophysics↗

Multiplexed bioluminescence microscopy via phasor analysis

Microscopic bioluminescence imaging has been historically challenging due to a lack of detection methods and easily resolved probes. Here we combine bioluminescence with phasor analysis, an optical method commonly used to distinguish spectrally similar fluorophores. Bioluminescent phasor enabled rapid differentiation of multiple luciferase reporters and resonance energy transfer processes. The merger of bioluminescence and phasor analysis provides a platform for routine, time-lapse imaging of collections of cellular features.

bioengineering↗

NAD consumption by PARP1 in response to DNA damage triggers metabolic shift critical for damaged cell survival

DNA damage signaling is critical for the maintenance of genome integrity and cell fate decision. Poly(ADP-ribose) polymerase 1 (PARP1) is a DNA damage sensor rapidly activated in a damage dose and complexity-dependent manner playing a critical role in the initial chromatin organization and DNA repair pathway choice at damage sites. However, the cell-wide consequence of its activation in damaged cells is not well delineated. Using the phasor approach to fluorescence lifetime imaging microscopy (FLIM) and fluorescence-based biosensors in combination with laser microirradiation, we found a rapid cell-wide increase of the bound/free NADH ratio in response to nuclear DNA damage, which is triggered by NAD+ depletion by PARP activation. This change is linked to the metabolic balance shift to oxidative phosphorylation (oxphos) over glycolysis. Inhibition of the respiratory chain resulted in rapid PARP-dependent ATP reduction and intracellular acidification, and eventually, PARP-dependent, AIF-independent, apoptosis indicating that oxphos becomes critical for damaged cell survival. The results reveal the novel pro-survival effect of PARP activation through a change in cellular metabolism, and demonstrate how unique applications of advanced fluorescence imaging technologies in combination with laser microirradiation can be a powerful tool to interrogate damage-induced metabolic changes at high spatiotemporal resolution in a live cell.

cell biology↗

Label-free assessment of pre-implantation embryo quality by the Fluorescence Lifetime Imaging Microscopy (FLIM)-phasor approach

Development of quantitative, safe and rapid techniques for assessing embryo quality provides significant advances in Assisted Reproductive Technologies (ART). We apply the phasor-FLIM method to capture endogenous fluorescent biomarkers of pre-implantation embryos as a non-morphological caliber for embryo quality. Here, we identify the developmental, or \"D-trajectory\", that consists of fluorescence lifetime from different stages of mouse pre-implantation embryos. The D-trajectory correlates with intrinsic fluorescent species from a distinctive energy metabolism and oxidized lipids, as seen with Third Harmonic Generation (THG) that changes over time. In addition, we have defined an Embryo Viability Index (EVI) to distinguish pre-implantation embryo quality using the Distance Analysis, a machine learning algorithm to process the fluorescence lifetime distribution patterns. We show that the phasor-FLIM approach provides a much-needed non-invasive quantitative technology for identifying healthy embryos at the early compaction stage with 86% accuracy. This may increase embryo implantation success for in vitro fertilization clinics.\n\nHighlightsO_LIA label-free method of tracking metabolic trajectories during pre-implantation mouse embryo development.\nC_LIO_LIA non-invasive approach for assessing embryo quality and viability by a phasor-FLIM analysis.\nC_LI

developmental biology↗