ChIP-GPT: a managed large language model for robust data extraction from biomedical database records.

Increasing volumes of biomedical data are amassing in databases. Large-scale analyses of these data have wide-ranging applications in biology and medicine. Such analyses require tools to characterize and process entries at scale. However, existing tools, mainly centered on extracting predefined fields, often fail to comprehensively process database entries or correct evident errors-a task humans can easily perform. These tools also lack the ability to reason like domain experts, hindering their robustness and analytical depth. Recent advances with large language models (LLMs) provide a fundamentally new way to query databases. But while a tool such as ChatGPT is adept at answering questions about manually input records, challenges arise when scaling up this process. First, interactions with the LLM need to be automated. Second, limitations on input length may require a record pruning or summarization pre-processing step. Third, to behave reliably as desired, the LLM needs either well-designed, short, 'few-shot' examples, or fine-tuning based on a larger set of well-curated examples. Here, we report ChIP-GPT, based on fine-tuning of the generative pre-trained transformer (GPT) model Llama and on a program prompting the model iteratively and handling its generation of answer text. This model is designed to extract metadata from the Sequence Read Archive, emphasizing the identification of chromatin immunoprecipitation (ChIP) targets and cell lines. When trained with 100 examples, ChIP-GPT demonstrates 90-94% accuracy. Notably, it can seamlessly extract data from records with typos or absent field labels. Our proposed method is easily adaptable to customized questions and different databases.

Flexizyme-aminoacylated shortened tRNAs demonstrate that only the aminoacylated acceptor arms of the two tRNA substrates are required for cyclodipeptide synthase activity.

Cyclodipeptide synthases (CDPSs) use two aminoacyl-tRNAs (AA-tRNAs) to catalyse cyclodipeptide formation in a ping-pong mechanism. Despite intense studies of these enzymes in past years, the tRNA regions of the two substrates required for CDPS activity are poorly documented, mainly because of two limitations. First, previously studied CDPSs use two identical AA-tRNAs to produce homocyclodipeptides, thus preventing the discriminative study of the binding of the two substrates. Second, the range of tRNA analogues that can be aminoacylated by aminoacyl-tRNA synthetases is limited. To overcome the limitations, we studied a new model CDPS that uses two different AA-tRNAs to produce an heterocyclodipeptide. We also developed a production pipeline for the production of purified shortened AA-tRNA analogues (AA-minitRNAs). This method combines the use of flexizymes to aminoacylate a diversity of minitRNAs and their subsequent purifications by anion-exchange chromatography. Finally, we were able to show that aminoacylated molecules mimicking the entire acceptor arms of tRNAs were as effective a substrate as entire AA-tRNAs, thereby demonstrating that the acceptor arms of the two substrates are the only parts of the tRNAs required for CDPS activity. The method developed in this study should greatly facilitate future investigations of the specificity of CDPSs and of other AA-tRNAs-utilizing enzymes.

Quantification of in vivo progenitor mutation accrual with ultra-low error rate and minimal input DNA using SIP-HAVA-seq.

Assaying in vivo accrual of DNA damage and DNA mutations by stem cells and pinpointing sources of damage and mutations would further our understanding of aging and carcinogenesis. Two main hurdles must be overcome. First, in vivo mutation rates are orders of magnitude lower than raw sequencing error rates. Second, stem cells are vastly outnumbered by differentiated cells, which have a higher mutation rate-quantification of stem cell DNA damage and DNA mutations is thus best performed from small, well-defined cell populations. Here we report a mutation detection technique, based on the "duplex sequencing" principle, with an error rate below ∼10-10 and that can start from as little as 50 pg DNA. We validate this technique, which we call SIP-HAVA-seq, by characterizing Caenorhabditis elegans germline stem cell mutation accrual and asking how mating affects that accrual. We find that a moderate mating-induced increase in cell cycling correlates with a dramatic increase in accrual of mutations. Intriguingly, these mutations consist chiefly of deletions in nonexpressed genes. This contrasts with results derived from mutation accumulation lines and suggests that mutation spectrum and genome distribution change with replicative age, chronological age, cell differentiation state, and/or overall worm physiological state. We also identify single-stranded gaps as plausible deletion precursors, providing a starting point to identify the molecular mechanisms of mutagenesis that are most active. SIP-HAVA-seq provides the first direct, genome-wide measurements of in vivo mutation accrual in stem cells and will enable further characterization of underlying mechanisms and their dependence on age and cell state.

Intermittent Stem Cell Cycling Balances Self-Renewal and Senescence of the C. elegans Germ Line.

Self-renewing organs often experience a decline in function in the course of aging. It is unclear whether chronological age or external factors control this decline, or whether it is driven by stem cell self-renewal-for example, because cycling cells exhaust their replicative capacity and become senescent. Here we assay the relationship between stem cell cycling and senescence in the Caenorhabditis elegans reproductive system, defining this senescence as the progressive decline in "reproductive capacity," i.e. in the number of progeny that can be produced until cessation of reproduction. We show that stem cell cycling diminishes remaining reproductive capacity, at least in part through the DNA damage response. Paradoxically, gonads kept under conditions that preclude reproduction keep cycling and producing cells that undergo apoptosis or are laid as unfertilized gametes, thus squandering reproductive capacity. We show that continued activity is in fact beneficial inasmuch as gonads that are active when reproduction is initiated have more sustained early progeny production. Intriguingly, continued cycling is intermittent-gonads switch between active and dormant states-and in all likelihood stochastic. Other organs face tradeoffs whereby stem cell cycling has the beneficial effect of providing freshly-differentiated cells and the detrimental effect of increasing the likelihood of cancer or senescence; stochastic stem cell cycling may allow for a subset of cells to preserve proliferative potential in old age, which may implement a strategy to deal with uncertainty as to the total amount of proliferation to be undergone over an organism's lifespan.

Gene Expression Noise Enhances Robust Organization of the Early Mammalian Blastocyst.

A critical event in mammalian embryo development is construction of an inner cell mass surrounded by a trophoectoderm (a shell of cells that later form extraembryonic structures). We utilize multi-scale, stochastic modeling to investigate the design principles responsible for robust establishment of these structures. This investigation makes three predictions, each supported by our quantitative imaging. First, stochasticity in the expression of critical genes promotes cell plasticity and has a critical role in accurately organizing the developing mouse blastocyst. Second, asymmetry in the levels of noise variation (expression fluctuation) of Cdx2 and Oct4 provides a means to gain the benefits of noise-mediated plasticity while ameliorating the potentially detrimental effects of stochasticity. Finally, by controlling the timing and pace of cell fate specification, the embryo temporally modulates plasticity and creates a time window during which each cell can continually read its environment and adjusts its fate. These results suggest noise has a crucial role in maintaining cellular plasticity and organizing the blastocyst.

BMP signaling is required for cell cleavage in preimplantation-mouse embryos.

The mechanisms regulating cell division during development of the mouse pre-implantation embryo are poorly understood. We have investigated whether bone morphogenetic protein (BMP) signaling is involved in controlling cell cycle during mouse pre-implantation development. We mapped and quantitated the dynamic activities of BMP signaling through high-resolution immunofluorescence imaging combined with a 3D segmentation method. Immunostaining for phosphorylated Smad1/5/8 shows that BMP signaling is activated in mouse embryos as early as the 4-cell stage, and becomes spatially restricted by late blastocyst stage. Perturbation of BMP signaling in preimplantation mouse embryos, whether by treatment with a small molecule inhibitor, with Noggin protein, or by overexpression of a dominant-negative BMP receptor, indicates that BMPs regulate cell cleavage up to the morula stage. These results indicate that BMP signaling is active during mouse pre-implantation development and is required for cell cleavage in preimplantation mouse embryos.

Control of Caenorhabditis elegans germ-line stem-cell cycling speed meets requirements of design to minimize mutation accumulation.

BACKGROUND: Stem cells are thought to play a critical role in minimizing the accumulation of mutations, but it is not clear which strategies they follow to fulfill that performance objective. Slow cycling of stem cells provides a simple strategy that can minimize cell pedigree depth and thereby minimize the accumulation of replication-dependent mutations. Although the power of this strategy was recognized early on, a quantitative assessment of whether and how it is employed by biological systems is missing. RESULTS: Here we address this problem using a simple self-renewing organ - the C. elegans gonad - whose overall organization is shared with many self-renewing organs. Computational simulations of mutation accumulation characterize a tradeoff between fast development and low mutation accumulation, and show that slow-cycling stem cells allow for an advantageous compromise to be reached. This compromise is such that worm germ-line stem cells should cycle more slowly than their differentiating counterparts, but only by a modest amount. Experimental measurements of cell cycle lengths derived using a new, quantitative technique are consistent with these predictions. CONCLUSIONS: Our findings shed light both on design principles that underlie the role of stem cells in delaying aging and on evolutionary forces that shape stem-cell gene regulatory networks.

POPE: post optimization posterior evaluation of likelihood free models.

BACKGROUND: In many domains, scientists build complex simulators of natural phenomena that encode their hypotheses about the underlying processes. These simulators can be deterministic or stochastic, fast or slow, constrained or unconstrained, and so on. Optimizing the simulators with respect to a set of parameter values is common practice, resulting in a single parameter setting that minimizes an objective subject to constraints. RESULTS: We propose algorithms for post optimization posterior evaluation (POPE) of simulators. The algorithms compute and visualize all simulations that can generate results of the same or better quality than the optimum, subject to constraints. These optimization posteriors are desirable for a number of reasons among which are easy interpretability, automatic parameter sensitivity and correlation analysis, and posterior predictive analysis. Our algorithms are simple extensions to an existing simulation-based inference framework called approximate Bayesian computation. POPE is applied two biological simulators: a fast and stochastic simulator of stem-cell cycling and a slow and deterministic simulator of tumor growth patterns. CONCLUSIONS: POPE allows the scientist to explore and understand the role that constraints, both on the input and the output, have on the optimization posterior. As a Bayesian inference procedure, POPE provides a rigorous framework for the analysis of the uncertainty of an optimal simulation parameter setting.

Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

BACKGROUND: Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge. RESULTS: Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels. CONCLUSIONS: High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.

Phasor approach to fluorescence lifetime microscopy distinguishes different metabolic states of germ cells in a live tissue.

We describe a label-free imaging method to monitor stem-cell metabolism that discriminates different states of stem cells as they differentiate in living tissues. In this method we use intrinsic fluorescence biomarkers and the phasor approach to fluorescence lifetime imaging microscopy in conjunction with image segmentation, which we use to introduce the concept of the cell phasor. In live tissues we are able to identify intrinsic fluorophores, such as collagen, retinol, retinoic acid, porphyrin, flavins, and free and bound NADH. We have exploited the cell phasor approach to detect a trend in metabolite concentrations along the main axis of the Caenorhabditis elegans germ line. This trend is consistent with known changes in metabolic states during differentiation. The cell phasor approach to lifetime imaging provides a label-free, fit-free, and sensitive method to identify different metabolic states of cells during differentiation, to sense small changes in the redox state of cells, and may identify symmetric and asymmetric divisions and predict cell fate. Our method is a promising noninvasive optical tool for monitoring metabolic pathways during differentiation or disease progression, and for cell sorting in unlabeled tissues.

Progression from a stem cell-like state to early differentiation in the C. elegans germ line.

Controls of stem cell maintenance and early differentiation are known in several systems. However, the progression from stem cell self-renewal to overt signs of early differentiation is a poorly understood but important problem in stem cell biology. The Caenorhabditis elegans germ line provides a genetically defined model for studying that progression. In this system, a single-celled mesenchymal niche, the distal tip cell (DTC), employs GLP-1/Notch signaling and an RNA regulatory network to balance self-renewal and early differentiation within the "mitotic region," which continuously self-renews while generating new gametes. Here, we investigate germ cells in the mitotic region for their capacity to differentiate and their state of maturation. Two distinct pools emerge. The "distal pool" is maintained by the DTC in an essentially uniform and immature or "stem cell-like" state; the "proximal pool," by contrast, contains cells that are maturing toward early differentiation and are likely transit-amplifying cells. A rough estimate of pool sizes is 30-70 germ cells in the distal immature pool and approximately 150 in the proximal transit-amplifying pool. We present a simple model for how the network underlying the switch between self-renewal and early differentiation may be acting in these two pools. According to our model, the self-renewal mode of the network maintains the distal pool in an immature state, whereas the transition between self-renewal and early differentiation modes of the network underlies the graded maturation of germ cells in the proximal pool. We discuss implications of this model for controls of stem cells more broadly.

Purpose and regulation of stem cells: a systems-biology view from the Caenorhabditis elegans germ line.

Stem cells are expected to play a key role in the development and maintenance of organisms, and hold great therapeutic promises. However, a number of questions must be answered to achieve an understanding of stem cells and put them to use. Here I review some of these questions, and how they relate to the model system provided by the Caenorhabditis elegans germ line, which is exceptional in its thorough genetic characterization and experimental accessibility under in vivo conditions. A fundamental question is how to define a stem cell; different definitions can be adopted that capture different features of interest. In the C. elegans germ line, stem cells can be defined by cell lineage or by cell commitment ('commitment' must itself be carefully defined). These definitions are associated with two other important questions about stem cells: their functions (which must be addressed following a systems approach, based on an evolutionary perspective) and their regulation. I review possible functions and their evolutionary groundings, including genome maintenance and powerful regulation of cell proliferation and differentiation, and possible regulatory mechanisms, including asymmetrical division and control of transit amplification by a developmental timer. I draw parallels between Drosophila and C. elegans germline stem cells; such parallels raise intriguing questions about Drosophila stem cells. I conclude by showing that the C. elegans germ line bears similarities with a number of other stem cell systems, which underscores its relevance to the understanding of stem cells.

More than just a pool.

An intricate stem cell niche boundary formed by finger-like extensions generates asymmetry in stem cell divisions.

Understanding the somitogenesis clock: what's missing?

The segmentation of vertebrate embryos depends on a complex genetic network that generates highly dynamic gene expression. Many of the elements of the network have been identified, but their interaction and their influence on segmentation remain poorly understood. A few mathematical models have been proposed to explain the dynamics of subsets of the network, but the mechanistic bases remain controversial. This review focuses on outstanding problems with the generation of somitogenesis clock oscillations, and the ways they could regulate segmentation. Proposals that oscillations are generated by a negative feedback loop formed by Lunatic fringe and Notch signaling are weighed against a model based on positive feedback, and the experimental basis for models of simple negative feedback involving Her/Hes genes or Wnt targets is evaluated. Differences are then made explicit between the many 'clock and wavefront' model variants that have been proposed to explain how the clock regulates segmentation. An understanding of the somitogenesis clock will require addressing experimentally the many questions that arise from the study of simple models.

Repressor dimerization in the zebrafish somitogenesis clock.

The oscillations of the somitogenesis clock are linked to the fundamental process of vertebrate embryo segmentation, yet little is known about their generation. In zebrafish, it has been proposed that Her proteins repress the transcription of their own mRNA. However, in its simplest form, this model is incompatible with the fact that morpholino knockdown of Her proteins can impair expression of their mRNA. Simple self-repression models also do not account for the spatiotemporal pattern of gene expression, with waves of gene expression shrinking as they propagate. Here we study computationally the networks generated by the wealth of dimerization possibilities amongst transcriptional repressors in the zebrafish somitogenesis clock. These networks can reproduce knockdown phenotypes, and strongly suggest the existence of a Her1-Her7 heterodimer, so far untested experimentally. The networks are the first reported to reproduce the spatiotemporal pattern of the zebrafish somitogenesis clock; they shed new light on the role of Her13.2, the only known link between the somitogenesis clock and positional information in the paraxial mesoderm. The networks can also account for perturbations of the clock by manipulation of FGF signaling. Achieving an understanding of the interplay between clock oscillations and positional information is a crucial first step in the investigation of the segmentation mechanism.

A new method to transfect the hypoblast of the chick embryo reveals conservation of the regulation of an Otx2 enhancer between mouse and chick extraembryonic endoderm.

BACKGROUND: The mouse anterior visceral endoderm (AVE) and the chick hypoblast are thought to have homologous roles in the early stages of neural induction and primitive streak formation. In mouse, many regulatory elements directing gene expression to the AVE have been identified. However, there is no technique to introduce DNA into the chick hypoblast that would enable a comparison of their activity and this has hampered a direct comparison of the regulation of gene expression in the mouse and chick extraembryonic endoderm. RESULTS: Here we describe a new method to introduce DNA into the chick hypoblast, using lipofectamine-mediated transfection. We show that the hypoblast can be easily transfected and that it starts to express a luciferase reporter within 2 hours of transfection. The validity of technique is tested by following the movement and fate of hypoblast cells, which reveals their translocation to the anterior germinal crescent. We then introduce a vector containing GFP driven by the mouse VEcis-Otx2 enhancer (which directs gene expression to the mouse AVE) and we detect activity in the hypoblast. CONCLUSION: The new technique for delivering expression constructs to the chick hypoblast will enable studies on gene activity and regulation to be performed in this tissue, which has proved difficult to transfect by electroporation. Our findings also reveal that regulatory elements that direct gene expression to the mouse AVE are active in chick hypoblast, supporting the idea that these two tissues have homologous functions.

Semi-permeable Diffusion Barriers Enhance Patterning Robustness in the C. elegans Germline.

Positional information derived from local morphogen concentration plays an important role in patterning. A key question is how morphogen diffusion and gene expression regulation shape positional information into an appropriate profile with suitably low noise. We address this question using a model system--the C. elegans germline--whose regulatory network has been well characterized genetically but whose spatiotemporal dynamics are poorly understood. We show that diffusion within the germline syncytium is a critical control of stem cell differentiation and that semi-permeable diffusion barriers present at key locations make it possible--in combination with a feedback loop in the germline regulatory network--for mitotic zone size to be robust against spatial noise in Notch signaling. Spatial averaging within compartments defined by diffusion barriers is an advantageous patterning strategy, which attenuates noise while still allowing for sharp transitions between compartments. This strategy could apply to other organs.

Roles of positive and negative feedback in biological systems.

We discuss the influence of positive and negative feedback on the stability of a system, which is not clear-cut, and involves complex, mathematical problems. We show in particular that positive feedback can have a stabilising effect on some systems. We also point out the role that positive feedback plays in the digital treatment of signals required by cellular signalling, drawing on analogies from electronics, and the role that negative feedback plays in making a system robust against alteration of its parameters. Both positive and negative feedback can be seen as important enhancers of the properties of biological systems.

Live imaging reveals active infiltration of mitotic zone by its stem cell niche.

Stem cells niches are increasingly recognized as dynamic environments that play a key role in transducing signals that allow an organism to exert control on its stem cells. Live imaging of stem cell niches in their in vivo setting is thus of high interest to dissect stem cell controls. Here we report a new microfluidic design that is highly amenable to dissemination in biology laboratories that have no microfluidics expertise. This design has allowed us to perform the first time lapse imaging of the C. elegans germline stem cell niche. Our results show that this niche is strikingly dynamic, and that morphological changes that take place during development are the result of a highly active process. These results lay the foundation for future studies to dissect molecular mechanisms by which stem cell niche morphology is modulated, and by which niche morphology controls stem cell behavior.

Generalized, switch-like competitive heterodimerization networks.

High-dimensional switches have been proposed as a way to model cellular differentiation, particularly in the context of basic Helix-Loop-Helix (bHLH) competitive heterodimerization networks. A previous study derived a simple rule showing how many elements can be co-expressed, depending on the rate of competition within the network. A limitation to that rule, however, is that many biochemical parameters were considered to be identical. Here, we derive a generalized rule. This in turns allows one to study more ways in which these networks could be regulated, linking intrinsic cellular differentiation determinants to extracellular cues.