Justin Barton, Aretas Gaspariunas, Jacob D Galson, Jinwoo Leem
{"title":"Building Representation Learning Models for Antibody Comprehension.","authors":"Justin Barton, Aretas Gaspariunas, Jacob D Galson, Jinwoo Leem","doi":"10.1101/cshperspect.a041462","DOIUrl":"10.1101/cshperspect.a041462","url":null,"abstract":"<p><p>Antibodies are versatile proteins with both the capacity to bind a broad range of targets and a proven track record as some of the most successful therapeutics. However, the development of novel antibody therapeutics is a lengthy and costly process. It is challenging to predict the functional and biophysical properties of antibodies from their amino acid sequence alone, requiring numerous experiments for full characterization. Machine learning, specifically deep representation learning, has emerged as a family of methods that can complement wet lab approaches and accelerate the overall discovery and engineering process. Here, we review advances in antibody sequence representation learning, and how this has improved antibody structure prediction and facilitated antibody optimization. We discuss challenges in the development and implementation of such models, such as the lack of publicly available, well-curated antibody function data and highlight opportunities for improvement. These and future advances in machine learning for antibody sequences have the potential to increase the success rate in developing new therapeutics, resulting in broader access to transformative medicines and improved patient outcomes.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910360/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138444148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Features, Fates, and Functions of Oligodendrocyte Precursor Cells.","authors":"Robert A Hill, Akiko Nishiyama, Ethan G Hughes","doi":"10.1101/cshperspect.a041425","DOIUrl":"10.1101/cshperspect.a041425","url":null,"abstract":"<p><p>Oligodendrocyte precursor cells (OPCs) are a central nervous system resident population of glia with a distinct molecular identity and an ever-increasing list of functions. OPCs generate oligodendrocytes throughout development and across the life span in most regions of the brain and spinal cord. This process involves a complex coordination of molecular checkpoints and biophysical cues from the environment that initiate the differentiation and integration of new oligodendrocytes that synthesize myelin sheaths on axons. Outside of their progenitor role, OPCs have been proposed to play other functions including the modulation of axonal and synaptic development and the participation in bidirectional signaling with neurons and other glia. Here, we review OPC identity and known functions and discuss recent findings implying other roles for these glial cells in brain physiology and pathology.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":6.9,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138486860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Agritech to Tame the Nitrogen Cycle.","authors":"Lisa Y Stein","doi":"10.1101/cshperspect.a041668","DOIUrl":"10.1101/cshperspect.a041668","url":null,"abstract":"<p><p>While the Haber-Bosch process for N-fixation has enabled a steady food supply for half of humanity, substantial use of synthetic fertilizers has caused a radical unevenness in the global N-cycle. The resulting increases in nitrate production and greenhouse gas (GHG) emissions have contributed to eutrophication of both ground and surface waters, the growth of oxygen minimum zones in coastal regions, ozone depletion, and rising global temperatures. As stated by the Food and Agriculture Organization of the United Nations, agriculture releases ∼9.3 Gt CO<sub>2</sub> equivalents per year, of which methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O) account for 5.3 Gt CO<sub>2</sub> equivalents. N-pollution and slowing the runaway N-cycle requires a combined effort to replace chemical fertilizers with biological alternatives, which after a 10-yr span of usage could eliminate a minimum of 30% of ag-related GHG emissions (∼1.59 Gt), protect waterways from nitrate pollution, and protect soils from further deterioration. Agritech solutions include bringing biological fertilizers and biological nitrification inhibitors to the marketplace to reduce the microbial conversion of fertilizer nitrogen into GHGs and other toxic intermediates. Worldwide adoption of these plant-derived molecules will substantially elevate nitrogen use efficiency by crops while blocking the dominant source of N<sub>2</sub>O to the atmosphere and simultaneously protecting the biological CH<sub>4</sub> sink. Additional agritech solutions to curtail N-pollution, soil erosion, and deterioration of freshwater supplies include soil-free aquaponics systems that utilize improved microbial inocula to enhance nitrogen use efficiency without GHG production. With adequate and timely investment and scale-up, microbe-based agritech solutions emphasizing N-cycling processes can dramatically reduce GHG emissions on short time lines.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41107067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emma L Berdan, Thomas G Aubier, Salvatore Cozzolino, Rui Faria, Jeffrey L Feder, Mabel D Giménez, Mathieu Joron, Jeremy B Searle, Claire Mérot
{"title":"Structural Variants and Speciation: Multiple Processes at Play.","authors":"Emma L Berdan, Thomas G Aubier, Salvatore Cozzolino, Rui Faria, Jeffrey L Feder, Mabel D Giménez, Mathieu Joron, Jeremy B Searle, Claire Mérot","doi":"10.1101/cshperspect.a041446","DOIUrl":"10.1101/cshperspect.a041446","url":null,"abstract":"<p><p>Research on the genomic architecture of speciation has increasingly revealed the importance of structural variants (SVs) that affect the presence, abundance, position, and/or direction of a nucleotide sequence. SVs include large chromosomal rearrangements such as fusion/fissions and inversions and translocations, as well as smaller variants such as duplications, insertions, and deletions (CNVs). Although we have ample evidence that SVs play a key role in speciation, the underlying mechanisms differ depending on the type and length of the SV, as well as the ecological, demographic, and historical context. We review predictions and empirical evidence for classic processes such as underdominance due to meiotic aberrations and the coupling effect of recombination suppression before exploring how recent sequencing methodologies illuminate the prevalence and diversity of SVs. We discuss specific properties of SVs and their impact throughout the genome, highlighting that multiple processes are at play, and possibly interacting, in the relationship between SVs and speciation.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138486863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variability in Neural Circuit Formation.","authors":"Kevin J Mitchell","doi":"10.1101/cshperspect.a041504","DOIUrl":"10.1101/cshperspect.a041504","url":null,"abstract":"<p><p>The study of neural development is usually concerned with the question of how nervous systems get put together. Variation in these processes is usually of interest as a means of revealing these normative mechanisms. However, variation itself can be an object of study and is of interest from multiple angles. First, the nature of variation in both the processes and the outcomes of neural development is relevant to our understanding of how these processes and outcomes are encoded in the genome. Second, variation in the wiring of the brain in humans may underlie variation in all kinds of psychological and behavioral traits, as well as neurodevelopmental disorders. And third, genetic variation that affects circuit development provides the raw material for evolutionary change. Here, I examine these different aspects of variation in circuit development and consider what they may tell us about these larger questions.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10910361/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139520227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mapping the Retina onto the Brain.","authors":"Daniel Kerschensteiner, Marla B Feller","doi":"10.1101/cshperspect.a041512","DOIUrl":"10.1101/cshperspect.a041512","url":null,"abstract":"<p><p>Vision begins in the retina, which extracts salient features from the environment and encodes them in the spike trains of retinal ganglion cells (RGCs), the output neurons of the eye. RGC axons innervate diverse brain areas (>50 in mice) to support perception, guide behavior, and mediate influences of light on physiology and internal states. In recent years, complete lists of RGC types (∼45 in mice) have been compiled, detailed maps of their dendritic connections drawn, and their light responses surveyed at scale. We know less about the RGCs' axonal projection patterns, which map retinal information onto the brain. However, some organizing principles have emerged. Here, we review the strategies and mechanisms that govern developing RGC axons and organize their innervation of retinorecipient brain areas.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10835620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138486862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Richard M Merrill, Henry Arenas-Castro, Anna F Feller, Julia Harenčár, Matteo Rossi, Matthew A Streisfeld, Kathleen M Kay
{"title":"Genetics and the Evolution of Prezygotic Isolation.","authors":"Richard M Merrill, Henry Arenas-Castro, Anna F Feller, Julia Harenčár, Matteo Rossi, Matthew A Streisfeld, Kathleen M Kay","doi":"10.1101/cshperspect.a041439","DOIUrl":"10.1101/cshperspect.a041439","url":null,"abstract":"<p><p>The significance of prezygotic isolation for speciation has been recognized at least since the Modern Synthesis. However, fundamental questions remain. For example, how are genetic associations between traits that contribute to prezygotic isolation maintained? What is the source of genetic variation underlying the evolution of these traits? And how do prezygotic barriers affect patterns of gene flow? We address these questions by reviewing genetic features shared across plants and animals that influence prezygotic isolation. Emerging technologies increasingly enable the identification and functional characterization of the genes involved, allowing us to test established theoretical expectations. Embedding these genes in their developmental context will allow further predictions about what constrains the evolution of prezygotic isolation. Ongoing improvements in statistical and computational tools will reveal how pre- and postzygotic isolation may differ in how they influence gene flow across the genome. Finally, we highlight opportunities for progress by combining theory with appropriate data.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":6.9,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10835618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41232994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kira Delmore, Hannah Justen, Kathleen M Kay, Jun Kitano, Leonie C Moyle, Rike Stelkens, Matthew A Streisfeld, Yo Y Yamasaki, Joseph Ross
{"title":"Genomic Approaches Are Improving Taxonomic Representation in Genetic Studies of Speciation.","authors":"Kira Delmore, Hannah Justen, Kathleen M Kay, Jun Kitano, Leonie C Moyle, Rike Stelkens, Matthew A Streisfeld, Yo Y Yamasaki, Joseph Ross","doi":"10.1101/cshperspect.a041438","DOIUrl":"10.1101/cshperspect.a041438","url":null,"abstract":"<p><p>Until recently, our understanding of the genetics of speciation was limited to a narrow group of model species with a specific set of characteristics that made genetic analysis feasible. Rapidly advancing genomic technologies are eliminating many of the distinctions between laboratory and natural systems. In light of these genomic developments, we review the history of speciation genetics, advances that have been gleaned from model and non-model organisms, the current state of the field, and prospects for broadening the diversity of taxa included in future studies. Responses to a survey of speciation scientists across the world reveal the ongoing division between the types of questions that are addressed in model and non-model organisms. To bridge this gap, we suggest integrating genetic studies from model systems that can be reared in the laboratory or greenhouse with genomic studies in related non-models where extensive ecological knowledge exists.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10835617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41232995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Photosynthesis 2.0: Realizing New-to-Nature CO<sub>2</sub>-Fixation to Overcome the Limits of Natural Metabolism.","authors":"Tobias J Erb","doi":"10.1101/cshperspect.a041669","DOIUrl":"10.1101/cshperspect.a041669","url":null,"abstract":"<p><p>Synthetic biology provides opportunities to realize new-to-nature CO<sub>2</sub>-fixation metabolisms to overcome the limitations of natural photosynthesis. Two different strategies are currently being pursued: One is to realize engineered plants that feature carbon-neutral or carbon-negative (i.e., CO<sub>2</sub>-fixing) photorespiration metabolism, such as the tatronyl-CoA (TaCo) pathway, to boost CO<sub>2</sub>-uptake rates of photosynthesis between 20% and 60%. Another (arguably more radical) is to create engineered plants in which natural photosynthesis is fully replaced by an alternative CO<sub>2</sub>-fixation metabolism, such as the CETCH cycle, which carries the potential to improve CO<sub>2</sub> uptake rates between 20% and 200%. These efforts could revolutionize plant engineering by expanding the capabilities of plant metabolism beyond the constraints of natural evolution to create highly improved crops addressing the challenges of climate change in the future.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10835606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41232996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Is Novelty Predictable?","authors":"Clara Fannjiang, Jennifer Listgarten","doi":"10.1101/cshperspect.a041469","DOIUrl":"10.1101/cshperspect.a041469","url":null,"abstract":"<p><p>Machine learning-based design has gained traction in the sciences, most notably in the design of small molecules, materials, and proteins, with societal applications ranging from drug development and plastic degradation to carbon sequestration. When designing objects to achieve novel property values with machine learning, one faces a fundamental challenge: how to push past the frontier of current knowledge, distilled from the training data into the model, in a manner that rationally controls the risk of failure. If one trusts learned models too much in extrapolation, one is likely to design rubbish. In contrast, if one does not extrapolate, one cannot find novelty. Herein, we ponder how one might strike a useful balance between these two extremes. We focus in particular on designing proteins with novel property values, although much of our discussion is relevant to machine learning-based design more broadly.</p>","PeriodicalId":10494,"journal":{"name":"Cold Spring Harbor perspectives in biology","volume":null,"pages":null},"PeriodicalIF":7.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10835614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138486861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}