Endogenous fluorescence signatures in living pluripotent stem cells change with loss of potency

Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions

Inflammatory arthritis, including rheumatoid (RA), and psoriatic (PsA) arthritis, are clinically and immunologically heterogeneous diseases with no identified cure. Chronic inflammation of the synovial tissue ushers loss of function of the joint that severely impacts the patient's quality of life, eventually leading to disability and life-threatening comorbidities. The pathogenesis of synovial inflammation is the consequence of compounded immune and stromal cell interactions influenced by genetic and environmental factors. Deciphering the complexity of the synovial cellular landscape has accelerated primarily due to the utilisation of bulk and single cell RNA sequencing. Particularly the capacity to generate cell-cell interaction networks could reveal evidence of previously unappreciated processes leading to disease. However, there is currently a lack of universal nomenclature as a result of varied experimental and technological approaches that discombobulates the study of synovial inflammation. While spatial transcriptomic analysis that combines anatomical information with transcriptomic data of synovial tissue biopsies promises to provide more insights into disease pathogenesis, in vitro functional assays with single-cell resolution will be required to validate current bioinformatic applications. In order to provide a comprehensive approach and translate experimental data to clinical practice, a combination of clinical and molecular data with machine learning has the potential to enhance patient stratification and identify individuals at risk of arthritis that would benefit from early therapeutic intervention. This review aims to provide a comprehensive understanding of the effect of computational approaches in deciphering synovial inflammation pathogenesis and discuss the impact that further experimental and novel computational tools may have on therapeutic target identification and drug development.

Establishment and characterization of a novel human induced pluripotent stem cell line stably expressing the iRFP720 reporter

Stem cell therapy has great potential for replacing beta-cell loss in diabetic patients. However, a key obstacle to cell therapy’s success is to preserve viability and function of the engrafted cells. While several strategies have been developed to improve engrafted beta-cell survival, tools to evaluate the efficacy within the body by imaging are limited. Traditional labeling tools, such as GFP-like fluorescent proteins, have limited penetration depths in vivo due to tissue scattering and absorption. To circumvent this limitation, a near-infrared fluorescent mutant version of the DrBphP bacteriophytochrome, iRFP720, has been developed for in vivo imaging and stem/progenitor cell tracking. Here, we present the generation and characterization of an iRFP720 expressing human induced pluripotent stem cell (iPSC) line, which can be used for real-time imaging in various biological applications. To generate the transgenic cells, the CRISPR/Cas9 technology was applied. A puromycin resistance gene was inserted into the AAVS1 locus, driven by the endogenous PPP1R12C promoter, along with the CAG-iRFP720 reporter cassette, which was flanked by insulator elements. Proper integration of the transgene into the targeted genomic region was assessed by comprehensive genetic analysis, verifying precise genome editing. Stable expression of iRFP720 in the cells was confirmed and imaged by their near-infrared fluorescence. We demonstrated that the reporter iPSCs exhibit normal stem cell characteristics and can be efficiently differentiated towards the pancreatic lineage. As the genetically modified reporter cells show retained pluripotency and multilineage differentiation potential, they hold great potential as a cellular model in a variety of biological and pharmacological applications.

Engineering hydrogels for personalized disease modeling and regenerative medicine

Technological innovations and advances in scientific understanding have created an environment where data can be collected, analyzed, and interpreted at scale, ushering in the era of personalized medicine. The ability to isolate cells from individual patients offers tremendous promise if those cells can be used to generate functional tissue replacements or used in disease modeling to determine optimal treatment strategies. Here, we review recent progress in the use of hydrogels to create artificial cellular microenvironments for personalized tissue engineering and regenerative medicine applications, as well as to develop personalized disease models. We highlight engineering strategies to control stem cell fate through hydrogel design, and the use of hydrogels in combination with organoids, advanced imaging methods, and novel bioprinting techniques to generate functional tissues. We also discuss the use of hydrogels to study molecular mechanisms underlying diseases and to create personalized in vitro disease models to complement existing pre-clinical models. Continued progress in the development of engineered hydrogels, in combination with other emerging technologies, will be essential to realize the immense potential of personalized medicine. STATEMENT OF SIGNIFICANCE: In this review, we cover recent advances in hydrogel engineering strategies with applications in personalized medicine. Specifically, we focus on material systems to expand or control differentiation of patient-derived stem cells, and hydrogels to reprogram somatic cells to pluripotent states. We then review applications of hydrogels in developing personalized engineered tissues. We also highlight the use of hydrogel systems as personalized disease models, focusing on specific examples in fibrosis and cancer, and more broadly on drug screening strategies using patient-derived cells and hydrogels. We believe this review will be a valuable contribution to the Special Issue and the readership of Acta Biomaterialia will appreciate the comprehensive overview of the utility of hydrogels in the developing field of personalized medicine.

Disease-Relevant Single Cell Photonic Signatures Identify S100β Stem Cells and their Myogenic Progeny in Vascular Lesions

A hallmark of subclinical atherosclerosis is the accumulation of vascular smooth muscle cell (SMC)-like cells leading to intimal thickening and lesion formation. While medial SMCs contribute to vascular lesions, the involvement of resident vascular stem cells (vSCs) remains unclear. We evaluated single cell photonics as a discriminator of cell phenotype in vitro before the presence of vSC within vascular lesions was assessed ex vivo using supervised machine learning and further validated using lineage tracing analysis. Using a novel lab-on-a-Disk(Load) platform, label-free single cell photonic emissions from normal and injured vessels ex vivo were interrogated and compared to freshly isolated aortic SMCs, cultured Movas SMCs, macrophages, B-cells, S100β⁺ mVSc, bone marrow derived mesenchymal stem cells (MSC) and their respective myogenic progeny across five broadband light wavelengths (λ465 - λ670 ± 20 nm). We found that profiles were of sufficient coverage, specificity, and quality to clearly distinguish medial SMCs from different vascular beds (carotid vs aorta), discriminate normal carotid medial SMCs from lesional SMC-like cells ex vivo following flow restriction, and identify SMC differentiation of a series of multipotent stem cells following treatment with transforming growth factor beta 1 (TGF- β1), the Notch ligand Jagged1, and Sonic Hedgehog using multivariate analysis, in part, due to photonic emissions from enhanced collagen III and elastin expression. Supervised machine learning supported genetic lineage tracing analysis of S100β⁺ vSCs and identified the presence of S100β⁺vSC-derived myogenic progeny within vascular lesions. We conclude disease-relevant photonic signatures may have predictive value for vascular disease.

Multiparameter flow cytometric detection and quantification of senescent cells in vitro

It has been over half a century since cellular senescence was first noted and characterized, and yet no consensus senescent marker has been reliably established. This challenge is compounded by the complexity and heterogenic phenotypes of senescent cells. This necessitates the use of multiple biomarkers to confidently characterise senescent cells. Despite cytochemical staining of senescence associated-beta-galactosidase being a single marker approach, as well as being time and labour-intensive, it remains the most popular detection method. We have developed an alternative flow cytometry-based method that simultaneously quantifies multiple senescence markers at a single-cell resolution. In this study, we applied this assay to the quantification of both replicative and induced senescent primary cells. Using this assay, we were able to quantify the activity level of SA β-galactosidase, the expression level of p16^INK4a and γH2AX in these cell populations. Our results show this flow cytometric approach to be sensitive, robust, and consistent in discriminating senescent cells in different cell senescence models. A strong positive correlation between these commonly- used senescence markers was demonstrated. The method described in this paper can easily be scaled up to accommodate high-throughput screening of senescent cells in applications such as therapeutic cell preparation, and in therapy-induced senescence following cancer treatment.

Autofluorescence is a Reliable in vitro Marker of Cellular Senescence in Human Mesenchymal Stromal Cells

Mesenchymal stromal cells (MSC) are used in cell therapies, however cellular senescence increases heterogeneity of cell populations and leads to uncertainty in therapies’ outcomes. The determination of cellular senescence is time consuming and logistically intensive. Here, we propose the use of endogenous autofluorescence as real-time quantification of cellular senescence in human MSC, based on label-free flow cytometry analysis. We correlated cell autofluorescence to senescence using senescence-associated beta-galactosidase assay (SA-β-Gal) with chromogenic (X-GAL) and fluorescent (C₁₂FDG) substrates, gene expression of senescence markers (such as p16^INK4A, p18^INK4C, CCND2 and CDCA7) and telomere length. Autofluorescence was further correlated to MSC differentiation assays (adipogenesis, chondrogenesis and osteogenesis), MSC stemness markers (CD90/CD106) and cytokine secretion (IL-6 and MCP-1). Increased cell autofluorescence significantly correlated with increased SA-β-Gal signal (both X-GAL and C₁₂FDG substrates), cell volume and cell granularity, IL-6/MCP-1 secretion and with increased p16^INK4A and CCND2 gene expression. Increased cell autofluorescence was negatively associated with the expression of the CD90/CD106 markers, osteogenic and chondrogenic differentiation potentials and p18^INK4C and CDCA7 gene expression. Cell autofluorescence correlated neither with telomere length nor with adipogenic differentiation potential. We conclude that autofluorescence can be used as fast and non-invasive senescence assay for comparing MSC populations under controlled culture conditions.

Autofluorescence lifetime imaging of cellular metabolism: Sensitivity toward cell density, pH, intracellular, and intercellular heterogeneity

Autofluorescence imaging (AFI) has greatly accelerated in the last decade, way past its origins in detecting endogenous signals in biological tissues to identify differences between samples. There are many endogenous fluorescence sources of contrast but the most robust and widely utilized have been those associated with metabolism. The intrinsically fluorescent metabolic cofactors nicotinamide adenine dinucleotide (NAD+ /NADH) and flavin adenine dinucleotide (FAD/FADH2 ) have been utilized in a number of AFI applications including basic research, clinical, and pharmaceutical studies. Fluorescence lifetime imaging microscopy (FLIM) has emerged as one of the more powerful AFI tools for NADH and FAD characterization due to its unique ability to noninvasively detect metabolite bound and free states and quantitate cellular redox ratio. However, despite this widespread biological use, many standardization methods are still needed to extend FLIM-based AFI into a fully robust research and clinical diagnostic tools. FLIM is sensitive to a wide range of factors in the fluorophore microenvironment, and there are a number of analysis variables as well. To this end, there has been an emphasis on developing imaging standards and ways to make the image acquisition and analysis more consistent. However, biological conditions during FLIM-based AFI imaging are rarely considered as key sources of FLIM variability. Here, we present several experimental factors with supporting data of the cellular microenvironment such as confluency, pH, inter-/intracellular heterogeneity, and choice of cell line that need to be considered for accurate quantitative FLIM-based AFI measurement of cellular metabolism. © 2018 International Society for Advancement of Cytometry.

Laser Tweezers Raman Microspectroscopy of Single Cells and Biological Particles

Laser tweezers Raman spectroscopy (LTRS) is a variation of micro-Raman spectroscopy that is used to analyze single cells and biological particles suspended in an aqueous environment. The Raman spectrum of the cell/particle reflects its intrinsic biochemical composition and molecular structures. The technique utilizes a laser trap generated by a tightly focused Gaussian laser beam to physically manipulate individual cells and immobilize them in the laser focal volume. The same laser that is used for optical trapping also simultaneously excites Raman signals from the trapped cell, which are detected using a spectrometer and a confocal detection setup. LTRS offers unique capabilities not commonly found in other optical cytometry methods, such as label-free chemical analysis, multi-parametric chemical detection with a single excitation laser, and a non-photobleaching signal that can be used to quantitate and monitor dynamic chemical changes. This chapter provides guidelines on the design of a single beam LTRS microscope and methods for building and aligning the system. Operating procedures for trapping particles and acquiring spectra and a summary of data analysis techniques are provided.

Multiphoton autofluorescence lifetime imaging of induced pluripotent stem cells

The multiphoton fluorescence lifetime imaging tomograph MPTflex with its flexible 360-deg scan head, articulated arm, and tunable femtosecond laser source was employed to study induced pluripotent stem cell (iPS) cultures. Autofluorescence (AF) lifetime imaging was performed with 250-ps temporal resolution and submicron spatial resolution using time-correlated single-photon counting. The two-photon excited AF was based on the metabolic coenzymes NAD(P)H and flavin adenine dinucleotide/flavoproteins. iPS cells generated from mouse embryonic fibroblasts (MEFs) and cocultured with growth-arrested MEFs as feeder cells have been studied. Significant differences on AF lifetime signatures were identified between iPS and feeder cells as well as between their differentiating counterparts.

Simple Monolayer Differentiation of Murine Cardiomyocytes via Nutrient Deprivation-Mediated Activation of β-Catenin

Methods to generate murine cardiomyocytes from pluripotent stem cells (PSCs) in vitro are resource and time intensive. All current protocols require exogenously provided soluble factors and almost all utilize embryoid body formation to modulate pathways associated with mesoderm specification and cardiomyocyte differentiation. Here, we developed a simple protocol without EBs and without exogenous soluble factors that enabled cardiomyocyte differentiation of a murine induced PSC line based on controlled nutrient deprivation in 2D monolayer cultures. We showed that this protocol reproducibly imposed metabolic stress and consequently modulated active β-catenin levels to yield functional cardiomyocytes. The yield of cardiomyocytes and calcium handling kinetics were comparable to existing approaches. However, this approach did not produce consistent results between murine PSC lines suggesting signaling pathways linking nutrient deprivation to β-catenin activation are not universally conserved and may be a remnant of the parent population from which the induced PSCs were derived.

Endogenous Optical Signals Reveal Changes of Elastin and Collagen Organization During Differentiation of Mouse Embryonic Stem Cells

Components of the extracellular matrix (ECM) have recently been shown to influence stem cell specification. However, it has been challenging to assess the spatial and temporal dynamics of stem cell-ECM interactions because most methodologies utilized to date require sample destruction or fixation. We examined the efficacy of utilizing the endogenous optical signals of two important ECM proteins, elastin (Eln), through autofluorescence, and type I collagen (ColI), through second harmonic generation (SHG), during mouse embryonic stem cell differentiation. After finding favorable overlap between antibody labeling and the endogenous fluorescent signal of Eln, we used this endogenous signal to map temporal changes in Eln and ColI during murine embryoid body differentiation and found that Eln increases until day 9 and then decreases slightly by day 12, while Col1 steadily increases over the 12-day period. Furthermore, we combined endogenous fluorescence imaging and SHG with antibody labeling of cardiomyocytes to examine the spatial relationship between Eln and ColI accumulation and cardiomyocyte differentiation. Eln was ubiquitously present, with enrichment in regions with cardiomyocyte differentiation, while there was an inverse correlation between ColI and cardiomyocyte differentiation. This work provides an important first step for utilizing endogenous optical signals, which can be visualized in living cells, to understand the relationship between the ECM and cardiomyocyte development and sets the stage for future studies of stem cell-ECM interactions and dynamics relevant to stem cells as well as other cell and tissue types.

Noninvasive sorting of stem cell aggregates based on intrinsic markers

Noninvasive biomarkers hold important potential for the characterization and purification of stem cells because the addition of exogenous labels, probes, or reporters, as well as the disruption of cell-cell and cell-extracellular matrix interactions, can unintentionally but dramatically alter stem cell state. We recently showed that intensity of the intrinsically fluorescent metabolite, nicotinamide adenine dinucleotide (NADH), fluctuates predictably with changes in stem cell viability and differentiation state. Here, we use multiphoton flow cytometry developed in our laboratory to rapidly and noninvasively characterize and purify populations of intact stem cell aggregates based on NADH intensity and assessed the differentiation capacity of sorted populations. We found removal of aggregates with NADH intensity indicative of cell death resulted in a remaining population of aggregates significantly more likely to produce beating cardiomyocytes (26% vs. 8%, P < 0.05). Similarly, we found isolation of stem cell aggregates with NADH intensity indicative of future cardiac differentiation gave rise to more aggregates with beating cardiomyocytes at later time points (50% vs. 28%, P < 0.05). Further, coupling NADH intensity with gating based on size, enhances the enrichment for EBs capable of giving rise to cardiomyocytes (59% vs. 27%, P < 0.05). Thus, we demonstrate that endogenous properties of cell aggregates, such as NADH and size, can serve as gating parameters for large particle sorting devices to purify populations of stem cells or their progeny in a noninvasive manner, leading the way for improved therapeutic applications.

Fluorescence lifetime imaging of alterations to cellular metabolism by domain 2 of the hepatitis C virus core protein

Hepatitis C virus (HCV) co-opts hepatic lipid pathways to facilitate its pathogenesis. The virus alters cellular lipid biosynthesis and trafficking, and causes an accumulation of lipid droplets (LDs) that gives rise to hepatic steatosis. Little is known about how these changes are controlled at the molecular level, and how they are related to the underlying metabolic states of the infected cell. The HCV core protein has previously been shown to independently induce alterations in hepatic lipid homeostasis. Herein, we demonstrate, using coherent anti-Stokes Raman scattering (CARS) microscopy, that expression of domain 2 of the HCV core protein (D2) fused to GFP is sufficient to induce an accumulation of larger lipid droplets (LDs) in the perinuclear region. Additionally, we performed fluorescence lifetime imaging of endogenous reduced nicotinamide adenine dinucleotides [NAD(P)H], a key coenzyme in cellular metabolic processes, to monitor changes in the cofactor’s abundance and conformational state in D2-GFP transfected cells. When expressed in Huh-7 human hepatoma cells, we observed that the D2-GFP induced accumulation of LDs correlated with an increase in total NAD(P)H fluorescence and an increase in the ratio of free to bound NAD(P)H. This is consistent with an approximate 10 fold increase in cellular NAD(P)H levels. Furthermore, the lifetimes of bound and free NAD(P)H were both significantly reduced – indicating viral protein-induced alterations in the cofactors’ binding and microenvironment. Interestingly, the D2-expressing cells showed a more diffuse localization of NAD(P)H fluorescence signal, consistent with an accumulation of the co-factor outside the mitochondria. These observations suggest that HCV causes a shift of metabolic control away from the use of the coenzyme in mitochondrial electron transport and towards glycolysis, lipid biosynthesis, and building of new biomass. Overall, our findings demonstrate that HCV induced alterations in hepatic metabolism is tightly linked to alterations in NAD(P)H functional states.