Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells.

Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or tipping point at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as “autofluorescence signatures” during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.</p

Shared Resource Laboratory Operations: Changes Made During Initial Global COVID-19 Lockdown of 2020

Undoubtedly, the global pandemic caused by the SARS-CoV-2 virus has had a significant impact on Shared Resource Laboratories (SRL) operations worldwide. Unlike other crises (e.g., natural disasters, acts of war, or terrorism) which often result in a sudden and sustained cessation of scientific research usually affecting one or two cities at a time, this impact is being seen simultaneously in every SRL worldwide albeit to a varying degree. The alterations to SRL operations caused by the COVID-19 pandemic can generally be divided into three categories: (1) complete shutdown, (2) partial shutdown, and (3) uninterrupted operations. In many cases, SRLs that remained partially or fully operational during the initial wave of global infections saw a concurrent increase in COVID-19-related research coming through their facilities. This forced SRLs to make rapid adjustments to core operations at the same time as infectious disease experts were still developing recommendations for the safety of frontline medical workers. Although many SRLs already had contingency plans in place, this pandemic has highlighted the importance of having such plans for continuity of service, if possible, during a crisis. Immediate changes have occurred in the way SRLs operate due to potential virus transmission and in line with this new “Best Practices” have been established, that is,social distancing, remote working, and technology-based meetings and training. Many of these changes are likely to be in place for some time with the threat of further waves of infections toward the end of 2020 and into 2021. Some of these best practices, such as having many training resources recorded and available online, are likely to remain long-term. Although many changes have been made in haste, these will alter the future operations of SRLs. In addition, we have learnt how to deal with future crises that may be encountered in the workplace