Tumors arise from uncontrolled cell proliferation driven by mutations in genes that regulate stem cell renewal and differentiation. Intestinal tumors, however, retain some hierarchical organization, maintaining both cancer stem cells (CSCs) and cancer differentiated cells (CDCs). This heterogeneity, coupled with cellular plasticity enabling CDCs to revert to CSCs, contributes to therapy resistance and relapse. Using genetically encoded fluorescent reporters in human tumor organoids, combined with our machine-learning-based cell tracker, CellPhenTracker, we simultaneously traced cell-type specification, metabolic changes, and reconstructed cell lineage trajectories during tumor organoid development. Our findings reveal distinctive metabolic phenotypes in CSCs and CDCs. We find that lactate regulates tumor dynamics, suppressing CSC differentiation and inducing dedifferentiation into a proliferative CSC state. Mechanistically, lactate increases histone acetylation, epigenetically activating MYC. Given that lactate's regulation of MYC depends on the bromodomain-containing protein 4 (BRD4), targeting cancer metabolism and BRD4 inhibitors emerge as a promising strategy to prevent tumor relapse.

Cell tracking is an indispensable tool for studying development by time-lapse imaging. However, existing cell trackers cannot assign confidence to predicted tracks, which prohibits fully automated analysis without manual curation. We present a fundamental advance: an algorithm that combines neural networks with statistical physics to determine cell tracks with error probabilities for each step in the track. From these, we can obtain error probabilities for any tracking feature, from cell cycles to lineage trees, that function like P values in data interpretation. Our method, OrganoidTracker 2.0, greatly speeds up tracking analysis by limiting manual curation to rare low-confidence tracking steps. Importantly, it also enables fully automated analysis by retaining only high-confidence track segments, which we demonstrate by analyzing cell cycles and differentiation events at scale for thousands of cells in multiple intestinal organoids. Our approach brings cell dynamics-based organoid screening within reach and enables transparent reporting of cell-tracking results and associated scientific claims.

Protein complexes are pivotal to most cellular processes. Emerging evidence indicating dimer assembly by pairs of ribosomes suggests yet unknown folding mechanisms involving two nascent chains. Here, we show that co-translational ribosome pairing allows their nascent chains to ‘chaperone each other’, thus enabling the formation of coiled-coil homodimers from subunits that misfold individually. We developed an integrated single-molecule fluorescence and force spectroscopy approach to probe the folding and assembly of two nascent chains extending from nearby ribosomes, using the intermediate filament lamin as a model system. Ribosome proximity during early translation stages is found to be critical: when interactions between nascent chains are inhibited or delayed, they become trapped in stable misfolded states that are no longer assembly-competent. Conversely, early interactions allow the two nascent chains to nucleate native-like quaternary structures that grow in size and stability as translation advances. We conjecture that protein folding mechanisms enabled by ribosome cooperation are more broadly relevant to intermediate filaments and other protein classes.

Cellular fitness depends on multiple phenotypes that must be balanced during evolutionary adaptation. For instance, coordinating growth and motility is critical for microbial colonization and cancer invasiveness. In bacteria, these phenotypes are controlled by local regulators that target single operons, as well as by global regulators that impact hundreds of genes. However, how the different levels of regulation interact during evolution is unclear. Here, we measured in Escherichia coli how CRISPR-mediated knockdowns of global and local transcription factors impact growth and motility in three environments. We found that local regulators mostly modulate motility, whereas global regulators jointly modulate growth and motility. Simulated evolutionary trajectories indicate that local regulators are typically altered first to improve motility before global regulators adjust growth and motility following their trade-off. These findings highlight the role of pleiotropic regulators in the adaptation of multiple phenotypes.

Intestinal tuft cells are epithelial sentinels that trigger host defense upon detection of parasite-derived compounds. While they represent potent targets for immunomodulatory therapies in inflammation-driven intestinal diseases, their functioning and differentiation are poorly understood. Here, we reveal common intermediary transcriptomes among the previously described tuft-1 and tuft-2 subtypes in mouse and human. Tuft cell subtype-specific reporter knock-ins in organoids show that the two subtypes reflect successive post-mitotic maturation stages within the tuft cell lineage. In vitro stimulation with interleukin-4 and 13 is sufficient to fuel the generation of new Nrep+ tuft-1 cells, arising from tuft precursors (tuft-p). Subsequently, changes in crypt-villus signaling gradients, such as BMP, and cholinergic signaling, are required to advance maturation towards Chat+ tuft-2 phenotypes. Functionally, we find chemosensory capacity to increase during maturation. Our tuft subtype-specific reporters and optimized differentiation strategy in organoids provide a platform to study immune-related tuft cell subtypes and their unique chemosensory properties.

Cell extrusion is essential for homeostatic self-renewal of the intestinal epithelium. extrusion is thought to be triggered by crowding-induced compression of cells at the intestinal villus tip. In this study, we found instead that a local “tug-of-war” competition between contractile cells regulated extrusion in the intestinal epithelium. We combined quantitative live microscopy, optogenetic induction of tissue tension, genetic perturbation of myosin II activity, and local disruption of the basal cortex in mouse intestines and intestinal organoids. these approaches revealed that a dynamic actomyosin network generates tension throughout the intestinal villi, including the villus tip region. mechanically weak cells unable to maintain this tension underwent extrusion. thus, epithelial barrier integrity depends on intercellular mechanics.

Fluorescence live-cell microscopy is one of the most frequently used techniques to study dynamic processes in organoids. However, it is often limited by laborious fluorescent reporter engineering, limited numbers of fluorescence channels, and adverse phototoxicity and protein overexpression effects. Label-free imaging is a promising alternative but not yet established for 3D cultures. Here, we introduce LabelFreeTracker, a label-free machine-learning-based method to visualize the nuclei and membranes in bright-field images of 3D mouse intestinal organoids. The approach uses U-Net neural networks trained on the bright-field transmitted light and fluorescence images of mouse intestinal organoids as obtained by standard confocal microscopy. LabelFreeTracker frees up fluorescence channels to study fluorescent reporters and allows (semi-)automated quantification of cell movement, cell shape and volume changes, proliferation, differentiation, and lineage trees. This method greatly simplifies live-cell imaging of tissue dynamics and will accelerate screening of patient-derived organoids, for which reporter engineering is not feasible.

Chaperones are essential to the co-translational folding of most proteins. However, the principles of co-translational chaperone interaction throughout the proteome are poorly understood, as current methods are restricted to few substrates and cannot capture nascent protein folding or chaperone binding sites, precluding a comprehensive understanding of productive and erroneous protein biosynthesis. Here, by integrating genome-wide selective ribosome profiling, single-molecule tools, and computational predictions using AlphaFold we show that the binding of the main E. coli chaperones involved in co-translational folding, Trigger Factor (TF) and DnaK correlates with "unsatisfied residues" exposed on nascent partial folds - residues that have begun to form tertiary structure but cannot yet form all native contacts due to ongoing translation. This general principle allows us to predict their co-translational binding across the proteome based on sequence only, which we verify experimentally. The results show that TF and DnaK stably bind partially folded rather than unfolded conformers. They also indicate a synergistic action of TF guiding intra-domain folding and DnaK preventing premature inter-domain contacts, and reveal robustness in the larger chaperone network (TF, DnaK, GroEL). Given the complexity of translation, folding, and chaperone functions, our predictions based on general chaperone binding rules indicate an unexpected underlying simplicity.

Conformational control of nascent chains is poorly understood. Chaperones are known to stabilize, unfold, and disaggregate polypeptides away from the ribosome. In comparison, much less is known about the elementary conformational control mechanisms at the ribosome. Yet, proteins encounter major folding and aggregation challenges during translation. Here, using selective ribosome profiling and optical tweezers with correlated single-molecule fluorescence, with dihydrofolate reductase (DHFR) as a model system, we show that the Escherichia coli chaperone trigger factor (TF) accelerates nascent chain folding. TF scans nascent chains by transient binding events, and then locks into a stable binding mode as the chain collapses and folds. This interplay is reciprocal: TF binding collapses nascent chains and stabilizes partial folds, while nascent chain compaction prolongs TF binding. Ongoing translation controls these cooperative effects, with TF-accelerated folding depending on the emergence of a peptide segment that is central to the core DHFR beta-sheet. The folding acceleration we report here impacts processes that depend on folding occurring cotranslationally, including cotranslational protein assembly, protein aggregation, and translational pausing, and may be relevant to other domains of life.

BEST4/CA7+ cells of the human intestine were recently identified by single-cell RNA sequencing. While their gene expression profile predicts a role in electrolyte balance, BEST4/CA7+ cell function has not been explored experimentally owing to the absence of BEST4/CA7+ cells in mice and the paucity of human in vitro models. Here, we establish a protocol that allows the emergence of BEST4/CA7+ cells in human intestinal organoids. Differentiation of BEST4/CA7+ cells requires activation of Notch signaling and the transcription factor SPIB. BEST4/CA7+ cell numbers strongly increase in response to the cytokine interferon-γ, supporting a role in immunity. Indeed, we demonstrate that BEST4/CA7+ cells generate robust CFTR-mediated fluid efflux when stimulated with bacterial diarrhea-causing toxins and find the norepinephrine-ADRA2A axis as a potential mechanism in blocking BEST4/CA7+ cell-mediated fluid secretion. Our observations identify a central role of BEST4/CA7+ cells in fluid homeostasis in response to bacterial infections.

Guanylate-binding proteins (GBPs) are interferon-inducible guanosine triphosphate hydrolases (GTPases) mediating host defense against intracellular pathogens. Their antimicrobial activity hinges on their ability to self-associate and coat pathogen-associated compartments or cytosolic bacteria. Coat formation depends on GTPase activity but how nucleotide binding and hydrolysis prime coat formation remains unclear. Here, we report the cryo-electron microscopy structure of the full-length human GBP1 dimer in its guanine nucleotide-bound state and describe the molecular ultrastructure of the GBP1 coat on liposomes and bacterial lipopolysaccharide membranes. Conformational changes of the middle and GTPase effector domains expose the isoprenylated C terminus for membrane association. The α-helical middle domains form a parallel, crossover arrangement essential for coat formation and position the extended effector domain for intercalation into the lipopolysaccharide layer of gram-negative membranes. Nucleotide binding and hydrolysis create oligomeric scaffolds with contractile abilities that promote membrane extrusion and fragmentation. Our data offer a structural and mechanistic framework for understanding GBP1 effector functions in intracellular immunity.

The inherent stochasticity of metabolism raises a critical question for understanding homeostasis: are cellular processes regulated in response to internal fluctuations? Here, we show that, in E. coli cells under constant external conditions, catabolic enzyme expression continuously responds to metabolic fluctuations. The underlying regulatory feedback is enabled by the cyclic AMP (cAMP) and cAMP receptor protein (CRP) system, which controls catabolic enzyme expression based on metabolite concentrations. Using single-cell microscopy, genetic constructs in which this feedback is disabled, and mathematical modeling, we show how fluctuations circulate through the metabolic and genetic network at sub-cell-cycle timescales. Modeling identifies four noise propagation modes, including one specific to CRP regulation. Together, these modes correctly predict noise circulation at perturbed cAMP levels. The cAMP-CRP system may thus have evolved to control internal metabolic fluctuations in addition to external growth conditions. We conjecture that second messengers may more broadly function to achieve cellular homeostasis.

Single molecule techniques are particularly well suited for investigating the processes of protein folding and chaperone assistance. However, current assays provide only a limited perspective on the various ways in which the cellular environment can influence the folding pathway of a protein. In this study, a single molecule mechanical interrogation assay is developed and used to monitor protein unfolding and refolding within a cytosolic solution. This allows to test the cumulative topological effect of the cytoplasmic interactome on the folding process. The results reveal a stabilization against forced unfolding for partial folds, which are attributed to the protective effect of the cytoplasmic environment against unfolding and aggregation. This research opens the possibility of conducting single molecule molecular folding experiments in quasi-biological environments.

Organoids are a major new tool to study tissue renewal. However, characterizing the underlying differentiation dynamics remains challenging. Here, we developed TypeTracker, which identifies cell fates by AI-enabled cell tracking and propagating end point fates back along the branched lineage trees. Cells that ultimately migrate to the villus commit to their new type early, when still deep inside the crypt, with important consequences: (i) Secretory cells commit before terminal division, with secretory fates emerging symmetrically in sister cells. (ii) Different secretory types descend from distinct stem cell lineages rather than an omnipotent secretory progenitor. (iii) The ratio between secretory and absorptive cells is strongly affected by proliferation after commitment. (iv) Spatial patterning occurs after commitment through type-dependent cell rearrangements. This "commit-then-sort" model contrasts with the conventional conveyor belt picture, where cells differentiate by moving up the crypt-villus axis and hence raises new questions about the underlying commitment and sorting mechanisms.

The collapse of polypeptides is thought important to protein folding, aggregation, intrinsic disorder, and phase separation. However, whether polypeptide collapse is modulated in cells to control protein states is unclear. Here, using integrated protein manipulation and imaging, we show that the chaperonin GroEL-ES can accelerate the folding of proteins by strengthening their collapse. GroEL induces contractile forces in substrate chains, which draws them into the cavity and triggers a general compaction and discrete folding transitions, even for slow-folding proteins. This collapse enhancement is strongest in the nucleotide-bound states of GroEL and is aided by GroES binding to the cavity rim and by the amphiphilic C-terminal tails at the cavity bottom. Collapse modulation is distinct from other proposed GroEL-ES folding acceleration mechanisms, including steric confinement and misfold unfolding. Given the prevalence of collapse throughout the proteome, we conjecture that collapse modulation is more generally relevant within the protein quality control machinery.

While CRISPR-Cas defence mechanisms have been studied on a population level, their temporal dynamics and variability in individual cells have remained unknown. Using a microfluidic device, time-lapse microscopy and mathematical modelling, we studied invader clearance in Escherichia coli across multiple generations. We observed that CRISPR interference is fast with a narrow distribution of clearance times. In contrast, for invaders with escaping PAM mutations we found large cell-to-cell variability, which originates from primed CRISPR adaptation. Faster growth and cell division and higher levels of Cascade increase the chance of clearance by interference, while slower growth is associated with increased chances of clearance by priming. Our findings suggest that Cascade binding to the mutated invader DNA, rather than spacer integration, is the main source of priming heterogeneity. The highly stochastic nature of primed CRISPR adaptation implies that only subpopulations of bacteria are able to respond quickly to invading threats. We conjecture that CRISPR-Cas dynamics and heterogeneity at the cellular level are crucial to understanding the strategy of bacteria in their competition with other species and phages.

The chaperone heat shock protein 90 (Hsp90) is well known to undergo important conformational changes, which depend on nucleotide and substrate interactions. Conversely, how the conformations of its unstable and disordered substrates are affected by Hsp90 is difficult to address experimentally yet is central to its function. Here, using optical tweezers, we find that Hsp90 promotes local contractions in unfolded chains that drive their global compaction down to dimensions of folded states. This compaction has a gradual nature while showing small steps, is stimulated by ATP, and performs mechanical work against counteracting forces that expand the chain dimensions. The Hsp90 interactions suppress the formation of larger-scale folded, misfolded, and aggregated structures. The observations support a model in which Hsp90 alters client conformations directly by promoting local intra-chain interactions while suppressing distant ones. We conjecture that chain compaction may be central to how Hsp90 protects unstable clients and cooperates with Hsp70.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Molecular catch bonds are ubiquitous in biology and essential for processes like leucocyte extravasion¹ and cellular mechanosensing². Unlike normal (slip) bonds, catch bonds strengthen under tension. The current paradigm is that this feature provides ‘strength on demand³’, thus enabling cells to increase rigidity under stress^1,4–6. However, catch bonds are often weaker than slip bonds because they have cryptic binding sites that are usually buried^7,8. Here we show that catch bonds render reconstituted cytoskeletal actin networks stronger than slip bonds, even though the individual bonds are weaker. Simulations show that slip bonds remain trapped in stress-free areas, whereas weak binding allows catch bonds to mitigate crack initiation by moving to high-tension areas. This ‘dissociation on demand’ explains how cells combine mechanical strength with the adaptability required for shape change, and is relevant to diseases where catch bonding is compromised^7,9, including focal segmental glomerulosclerosis¹⁰ caused by the α-actinin-4 mutant studied here. We surmise that catch bonds are the key to create life-like materials.