The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive. Using time-series single cell RNA-seq of the bleomycin lung injury model, we resolved transcriptional dynamics for 28 cell types. Trajectory modeling together with lineage tracing revealed that airway and alveolar stem cells converge on a unique Krt8 + transitional stem cell state during alveolar regeneration. These cells have squamous morphology, feature p53 and NFkB activation and display transcriptional features of cellular senescence. The Krt8+ state appears in several independent models of lung injury and persists in human lung fibrosis, creating a distinct cell-cell communication network with mesenchyme and macrophages during repair. We generated a model of gene regulatory programs leading to Krt8+ transitional cells and their terminal differentiation to alveolar type-1 cells. We propose that in lung fibrosis, perturbed molecular checkpoints on the way to terminal differentiation can cause aberrant persistence of regenerative intermediate stem cell states.

Rheotaxis, the directed response to fluid velocity gradients, has been shown to facilitate stable upstream swimming of mammalian sperm cells along solid surfaces, suggesting a robust physical mechanism for long-distance navigation during fertilization. However, the dynamics by which a human sperm orients itself relative to an ambient flow is poorly understood. Here, we combine microfluidic experiments with mathematical modeling and 3D flagellar beat reconstruction to quantify the response of individual sperm cells in time-varying flow fields. Single-cell tracking reveals two kinematically distinct swimming states that entail opposite turning behaviors under flow reversal. We constrain an effective 2D model for the turning dynamics through systematic large-scale parameter scans, and find good quantitative agreement with experiments at different shear rates and viscosities. Using a 3D reconstruction algorithm to identify the flagellar beat patterns causing left or right turning, we present comprehensive 3D data demonstrating the rolling dynamics of freely swimming sperm cells around their longitudinal axis. Contrary to current beliefs, this 3D analysis uncovers ambidextrous flagellar waveforms and shows that the cell's turning direction is not defined by the rolling direction. Instead, the different rheotactic turning behaviors are linked to a broken mirror symmetry in the midpiece section, likely arising from a buckling instability. These results challenge current theoretical models of sperm locomotion.sperm swimming | rheotaxis | fluid dynamics | microfluidics | simulations T axis, the directed kinematic response to external signals, is a defining feature of living things that affects their reproduction, foraging, migration, and survival strategies (1-4). Higher organisms rely on sophisticated networks of finely tuned sensory mechanisms to move efficiently in the presence of chemical or physical stimuli. However, various fundamental forms of taxis are already manifest at the unicellular level, ranging from chemotaxis in bacteria (5) and phototaxis in unicellular green algae (2) to the mechanical response (durotaxis) of fibroblasts (6) and rheotaxis (7, 8) in spermatozoa (3, 9-12). Over the last few decades, much progress has been made in deciphering chemotactic, phototactic, and durotactic pathways in prokaryotic and eukaryotic model systems. In contrast, comparatively little is known about the physical mechanisms that enable flow gradient sensing in sperm cells (3, 9-13). Recent studies (3, 12) suggest that mammalian sperm use rheotaxis for long-distance navigation, but it remains unclear how shear flows alter flagellar beat patterns in the vicinity of surfaces and, in particular, how such changes in the beat dynamics affect the steering process. Answering these questions will be essential for evaluating the importance of chemical (14) and physical (4) signals during mammalian fertilization (15-17).A necessary requirement for any form of directed kinematic response is the ability to change the direction of loco...

Lung disease is a major health burden accounting for one in six deaths globally 1 . The lung's large surface area is exposed to a great variety of environmental and microbial insults causing injuries to its epithelium that require a regenerative response mediated by tissue-resident stem and progenitor Lung injury activates quiescent stem and progenitor cells to regenerate alveolar structures. The sequence and coordination of transcriptional programs during this process has largely remained elusive. Using single cell RNA-seq, we first generated a whole-organ bird's-eye view on cellular dynamics and cell-cell communication networks during mouse lung regeneration from ~30,000 cells at six timepoints. We discovered an injury-specific progenitor cell state characterized by Krt8 in flat epithelial cells covering alveolar surfaces. The number of these cells peaked during fibrogenesis in independent mouse models, as well as in human acute lung injury and fibrosis. Krt8+ progenitors featured a highly distinct connectome of receptor-ligand pairs with endothelial cells, fibroblasts, and macrophages. To 'sky dive' into epithelial differentiation dynamics, we sequenced >30,000 sorted epithelial cells at 18 timepoints and computationally derived cell state trajectories that were validated by lineage tracing genetic reporter mice. Airway stem cells within the club cell lineage and alveolar type-2 cells underwent transcriptional convergence onto the same Krt8+ progenitor cell state, which later resolved by terminal differentiation into alveolar type-1 cells. We derived distinct transcriptional regulators as key switch points in this process and show that induction of TNF-alpha/NFkappaB, p53, and hypoxia driven gene expression programs precede a Sox4, Ctnnb1, and Wwtr1 driven switch towards alveolar type-1 cell fate. We show that epithelial cell plasticity can induce non-gradual transdifferentiation, involving intermediate progenitor cell states that may persist and promote disease if checkpoint signals for terminal differentiation are perturbed.

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The formation and maintenance of subcellular structures and organelles with a well-defined size is a key requirement for cell function, yet our understanding of the underlying size control mechanisms is limited. While budding yeast cell polarization and subsequent assembly of a septin ring at the site of bud formation has been successfully used as a model for biological self-assembly processes, the mechanisms that set the size of the septin ring at the bud neck are unknown. Here, we use live-cell imaging and genetic manipulation of cell volume to show that the septin ring diameter increases with cell volume. This cell-volume-dependence largely accounts for modulations of ring size due to changes in ploidy and genetic manipulation of cell polarization. Our findings suggest that the ring diameter is set through the dynamic interplay of septin recruitment and Cdc42 polarization, establishing it as a model for size homeostasis of self-assembling organelles.

Nowadays droplet microfluidics is widely used to perform high throughput assays and for the synthesis of micro- and nanoparticles. These applications usually require packaging several reagents into droplets and their mixing to start a biochemical reaction. For rapid mixing microfluidic devices usually require additional functional elements that make their designs more complex. Here we perform a series of 2D numerical simulations, followed by experimental studies, and introduce a novel asymmetric flow-focusing droplet generator, which enhances mixing during droplet formation due to a 2D or 3D asymmetric vortex, located in the droplet formation area of the microfluidic device. Our results suggest that 2D numerical simulations can be used for qualitative analysis of two-phase flows and droplet generation process in quasi-two-dimensional devices, while the relative simplicity of such simulations allows them to be easily applied to fairly complicated microfluidic geometries. Mixing inside droplets formed in the asymmetric generator occurs up to six times faster than in a conventional symmetric one. The best mixing efficiency is achieved in a specific range of droplet volumes, which can be changed by scaling the geometry of the device. Thus, the droplet generator suggested here can significantly simplify designs of microfluidic devices because it enables both the droplet formation and fast mixing of the reagents within droplets. Moreover, it can be used to precisely estimate reaction kinetics.

Whi5 is diluted and protein synthesis does not dramatically increase in pre-Start G1The Whi5 dilution model requires that the concentration of Whi5 in newborn cells decreases with their cell size at birth, and that dilution by cell growth causes a continuous decrease of Whi5 concentration during G1. While the size-dependent Whi5 concentration at birth is based on an unusual cell size-independent transcriptional mechanism and chromatin-based partitioning (Schmoller et al., 2015;Swaffer et al., 2021), the latter is explained by two key observations. First, Whi5 is a stable protein (Schmoller et al., 2015;Gomar-Alba et al., 2017). Second, transcription of WHI5 mRNA is strongly cell cycle-dependent and peaks in S/G2 (Spellman et al., 1998;Pramila et al., 2006;Granovskaia et al., 2010). Indeed, it has long been known that WHI5 is a cell cycledependent transcript as it ranks among the top 300 most periodically expressed budding yeast genes in the Cyclebase database (Santos et al., 2015). This cell cycle dependence was recently confirmed using single molecule FISH (Qu et al., 2019;Swaffer et al., 2021). Thus, unless translational control perfectly compensates for the transcriptional oscillation, cell growth during G1-the period in which Whi5 mRNA is only weakly expressed-will inevitably decrease Whi5 protein concentration. Importantly, dilution of Whi5 does not imply that there is absolutely no synthesis of Whi5 protein during G1, just that its synthesis rate in G1 is significantly lower than in S/G2/M.Whi5 dilution during pre-Start G1 was observed using live-cell wide-field fluorescence microscopy of Whi5 in asynchronously cycling single cells (Schmoller et al., 2015). This analysis required careful subtraction of background and cell autofluorescence before the total fluorescence intensity of tagged Whi5 can be extracted as a proxy for the total amount of Whi5 protein. Simultaneous estimation of cell volume based on cell segmentations obtained from phase contrast images can then be used to calculate the relative change of Whi5 concentration over time. Using this approach, we found that Whi5 protein concentrations directly reflect its transcriptional regulation. In G1, Whi5 is weakly expressed, which leads to its dilution in this phase of the cell cycle. This is followed by a strong increase in Whi5 synthesis in the budded phase of the cell cycle (Schmoller et al., 2015).

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