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Results for “molecular biology”

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bioRxiv2022

Autophagy is associated with survival and resiliency of fibroblasts in long-term decaying post-mortem parenchymal tissue

Fibroblasts are spindle-shaped mesenchymal cells and an abundantly studied cell type that are easy to culture. Their adaptive response in culture conditions allows for use in many different cell biological experiments, including their utility in generating induced pluripotent stem cells. Despite extensive use of fibroblasts in cell and molecular biology and genetics experiments, fundamental evaluation of their resiliency and survival programs, in comparison with other cell types, is undetermined. Here, we demonstrate that fibroblasts exhibit remarkable survival capacity in post-mortem tissue decaying at room temperature and can be cultured from ear, tail tips, kidney, lung, fetal, and mammary tumor tissue after 12-hours of post-mortem tissue decay. Fibroblasts can be cultured from ear and lung tissue after 24-hours, and from ear after up to 120-hours of post-mortem tissue decay. Gene expression profiling of post-mortem lung tissue fibroblasts compared to fresh tissue cultured fibroblasts suggested a transition to a more quiescent phenotype with activation of nutrient scavenging pathways as evidenced by downregulation of genes associated with DNA replication, ribosomes, cell cycle, and spliceosomes as well as upregulation of genes associated metabolism, autophagy, and lysosomes. Measurement of light chain 3B (LC3B)-I/LC3B-II ratio and lysosomal-associated membrane protein (LAMP)-1 indicate that autophagy is increased in post-mortem fibroblasts, with evidence for potential increase in autolysosomes and senescence program. Our study provides evidence for the ability of normal fibroblasts to overcome extreme stress conditions and offers new insights into cell survival mechanisms and aging, with potential utility in tissue regeneration and repair.

cell biology↗

bioRxiv2020

Using single-plant -omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled lab environments. Over the years, lab experiments have generated substantial insights in the molecular wiring of plant developmental processes, stress responses and phenotypes. However, translating these insights from the lab to the field is often not straightforward, in part because field growth conditions are very different from lab conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field, and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional lab-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict at least some individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

systems biology↗

bioRxiv2023

Design of artificial molecular motor inheriting directionality and scalability.

Realizing artificial molecular motors with autonomous functionality and high performance is a major challenge in biophysics. Such motors not only provide new perspectives in biotechnology but also offer a novel approach for the bottom-up elucidation of biological molecular motors. Directionality and scalability are critical factors for practical applications. However, the simultaneous realization of both remains challenging. In this study, we propose a novel design for a rotary motor that can be fabricated using a currently available technology, DNA origami, and validate its functionality through simulations with practical parameters. We demonstrate that the motor rotates unidirectionally and processively in the direction defined by structural asymmetry, which induces kinetic asymmetry in motor motion. The motor also exhibits scalability, such that increasing the number of connections between the motor and stator allows for a larger speed, run length, and stall force. Statement of SignificanceBiological molecular motors are the most sophisticated nanomachines found in nature. Despite a long history of research, we have yet to understand how they work in detail. A simple and promising approach involves the building of artificial molecular motors. The process of achieving these goals helps us understand how the structures and mechanisms of the biological motors have been optimized through the evolution of their functions. Some artificial motors have already been achieved. However, each realization implements only a part of the characteristics of biological motors. In this work, we propose a novel motor mechanism that simultaneously implements two essential characteristics: scalability and directionality. These results will help us improve the biophysics of molecular motors and contribute to developing high-performance artificial molecular motors with possible industrial applications.

biophysics↗

bioRxiv2024

LucaOne: Generalized Biological Foundation Model with Unified Nucleic Acid and Protein Language

AbstractThe language of biology, encoded in DNA, RNA, and proteins, forms the foundation of life but remains challenging to decode due to its complexity. Traditional computational methods often struggle to integrate information across these molecules, limiting a comprehensive understanding of biological systems. Advances in Natural Language Processing (NLP) with pre-trained models offer new possibilities for interpreting biological language. Here, we introduce LucaOne, a pre-trained foundation model trained on nucleic acid and protein sequences from 169,861 species. Through large-scale data integration and semisupervised learning, LucaOne demonstrates an understanding of key biological principles, such as DNA-Protein translation. Using few-shot learning, it effectively comprehends the central dogma of molecular biology and performs competitively on tasks involving DNA, RNA, or protein inputs. Our results highlight the potential of unified foundation models to address complex biological questions, providing an adaptable framework for bioinformatics research and enhancing the interpretation of lifes complexity.

bioinformatics↗

bioRxiv2019

A HaloTag-TEV genetic cassette for mechanical phenotyping of native proteins

Single-molecule methods using recombinant proteins have generated transformative hypotheses on how mechanical forces are generated and sensed in biological tissues. However, testing these mechanical hypotheses on native molecules in their natural environment remains inaccessible to conventional genetics, biophysics and molecular biology tools. To address these limitations, here we demonstrate a genetically engineered knock-in mouse model carrying a HaloTag-TEV insertion in the protein titin, the main determinant of myocyte stiffness. Using our system, we have specifically severed the titin filament by digestion with TEV protease, and found that the response of muscle fibers to length changes requires mechanical transduction through titins intact polypeptide chain. HaloTag-based covalent tethering has enabled directed examination of the dynamics of titin under 1-100 pN forces using recently developed magnetic tweezers. At pulling forces lower than 10 pN, titin domains are readily recruited to the unfolded state, and produce 41.5 zJ mechanical work during refolding. Our results support an active role of titin in muscle contraction in coordination with actomyosin motors. Insertion of the HaloTag-TEV cassette in proteins with mechanical roles opens new grounds to explore the molecular basis of cellular force generation, mechanosensing and mechanotransduction.

biophysics↗

bioRxiv2023

Genome sequence and cell biological toolbox of the highly regenerative, coenocytic green feather alga Bryopsis

Green feather algae (Bryopsidales) undergo a unique life cycle in which a single cell repeatedly executes nuclear division without cytokinesis, resulting in the development of a thallus (> 100 mm) with characteristic morphology called coenocyte. Bryopsis is a representative coenocytic alga that has exceptionally high regeneration ability: extruded cytoplasm aggregates rapidly in seawater, leading to the formation of protoplasts. However, the genetic basis of the unique cell biology of Bryopsis remains poorly understood. Here, we present a high-quality assembly and annotation of the nuclear genome of Bryopsis sp. (90.7 Mbp, 27 contigs, N50 = 6.7 Mbp, 14,034 protein-coding genes). Comparative genomic analyses indicate that the genes encoding BPL-1/Bryohealin, the aggregation-promoting lectin, are heavily duplicated in Bryopsis, whereas homologous genes are absent in other Ulvophycean algae, suggesting the basis of regeneration capability of Bryopsis. Bryopsis sp. possesses >30 kinesins but only a single myosin, which differs from other green algae that have multiple types of myosin genes. Consistent with this biased motor toolkit, we observed that the bidirectional motility of chloroplasts in the cytoplasm was dependent on microtubules but not actin in Bryopsis sp. Unexpectedly, most genes required for cytokinesis in plants are present in Bryopsis, including those in the SNARE or kinesin superfamily. Nevertheless, a kinesin crucial for cytokinesis initiation in plants (NACK/Kinesin-7II) is hardly expressed in the coenocytic part of the thallus, possibly underlying the lack of cytokinesis in this portion. The present genome sequence lays the foundation for experimental biology in coenocytic macroalgae. Significance statementThe exceptionally coenocytic body and remarkable regeneration ability of Bryopsis have attracted biologists for years. However, molecular biological tools remain underdeveloped, partly due to the lack of genome information. Here, we report high-quality assembly and annotation of the genome, providing a crucial resource for experimental biology and genomics studies of Bryopsis. Furthermore, comparative genomic analysis reveals a unique gene repertoire that possibly underlies the highly regenerative coenocytic body.

plant biology↗

bioRxiv2024

Cross-species transmission of human hepatitis B virus to wild Neotropical primates

Hepatitis B virus (HBV) infects approximately one-third of the worlds human population and kills over one million people each year. HBV is also prevalent in Old World apes but not in New World primates. Human-to-primate transmission of HBV was suspected in zoo-captive monkeys and Mauritius macaques, but empirical data are scarce. Here, we collected blood and liver samples from 88 monkeys of 27 species in two areas of the Amazon, one with pristine forest and the other highly occupied and deforested by humans. A total of 17 (34.7%) out of 49 specimens from the human-occupied region tested positive for HBV. At this site, there was a positive relationship between human population density in the sampling location and the likelihood of primates being infected by HBV. Conversely, all 39 samples from the pristine forest tested negative for HBV. By sequencing a portion of the HBV S gene in five positive samples, each from a distinct primate genus, we found that four samples were closely related to the globally widespread human HBV-A strain, but not to the Americas-native HBV-F strain. The fifth sample aligned with the human HBV-D type, prevalent in the region where these samples were obtained. To our knowledge, this study represents the first reported cases of HBV in multiple wild New World primate species anywhere in the world. Our results suggest that primates were infected by strains brought into this part of Brazil by human immigrants, where HBV transmission may have been facilitated by the close contact between humans and monkeys due to high human occupation. This shows that the impact of human immigration, occupation and population growth in the Amazon extends beyond habitat loss; it also facilitates cross-species infections, potentially leading to the emergence of new, virulent viral strains that threaten both Amazonian biodiversity and human health. Author SummaryJean P. Boubli: Professor in Primate Ecology and Evolution, School of Science, Engineering and the Environment, University of Salford, Uk Hani R. El Bizri: PhD in Wildlife Conservation with a focus on Amazonian sustainable development. Analyst of Center for International Forestry Research (CIFOR), Bogor, Indonesia Luan F. Botelho-Souza: Masters and doctorate in experimental biology at the Universidade Federal de Rondonia/Brazil, Chrysoula Gubili: Researcher at the Fisheries Research Institute Nea Peramos, Kavala, Greece, specializing in population ecology and conservation genetics. Stephen J. Martin: Professor in Social Insects, School of Science, Engineering and the Environment, University of Salford, Uk Maisa da S. Araujo: Masters and doctorate in experimental biology, at the Universidade Federal de Rondonia/Brazil, Mariluce R. Messias: Professor of Zoology and curator of the Mammalogy Museum at the Universidade Federal de Rondonia/Brazil. Alcione de O. dos Santos: Masters and doctorate in experimental biology at the Universidade Federal de Rondonia/Brazil. Luiz S. Ozaki: Masters degree from Universidade de Brasilia and PhD in Physiological Sciences, Molecular Biology in Fukuoka, Kyushu, Japan. Andre V.C. Pereira: Bachelor in Biology the Universidade Federal de Rondonia/Brazil. Tony H. Katsuragawa: Masters and doctorate in experimental biology, at the Universidade Federal de Rondonia/Brazil. Ana Maisa Passos-Silva: Masters degree in experimental biology from the Federal University of Rondonia/Brazil. Luiz H. S. Gil: Masters in experimental biology, at the Universidade Federal de Rondonia/Brazil. Izeni P. Farias: Professor of Genetics, Universidade Federal do Amazonas, Brazil Juan M.V. Salcedo: Master in Tropical Medicine from the University of Brasilia/Brazil and PhD in Sciences from the University of Sao Paulo/Brazil. Tommy C. Burch: Masters in Biological Sciences and PhD candidate from the University of Salford, UK. Deusilene Vieira: Master in Tropical Medicine from the University of Brasilia/Brazil and PhD in Sciences from the University of Sao Paulo/Brazil.

pathology↗

bioRxiv2025

Catch & Release - rapid cost-effective protein purification from plants using a DIY GFP-Trap-protease approach

The purification of proteins is the foundation to study their structure, function, biochemical properties, and interaction partners. In plant research, unique challenges arise from the complexity of plant tissues, interference of secondary metabolites, and sometimes the low abundance of target proteins. Many conventional plant protein purification methods rely on expensive reagents, multi-step procedures, and labor-intensive workflows, limiting their feasibility for many applications. Here, we present the "Catch & Release" system, a cost-effective, fast and reliable one-step purification workflow for the isolation of soluble and membrane-bound proteins from plant tissues. The Catch & Release toolbox includes a vector set, a homemade GFP-trap and homemade proteases. Catch & Release vectors streamline cloning and transgenic plant selection through the Fluorescence-Accumulating Seed Technology (FAST), which marks positive transformants with a strongly fluorescing seed coat. Each plasmid consists of four, easy to exchange, modules: a plant promoter, a cloning dropout marker, protease cleavage sites, and seven different epitope tags, including an innovative dual-fluorescent tag, providing flexibility for diverse experimental needs. The in vivo functionality of all modules has been confirmed. Besides enabling standard molecular biological experimentation, our vector set in combination with homemade GFP-trap and proteases enables efficient and rapid isolation of soluble and high molecular weight membrane proteins directly from plants. By following our detailed reagent preparation instructions, purification costs can be decreased hundred-fold compared to the commercially available options.

plant biology↗

bioRxiv2020

Characterization and analysis of the transcriptome in Arapaima gigas using multi-tissue RNA-sequencing

Arapaima gigas is a giant bony tongue air-breathing fish, and a promising species for aquaculture due to its particular features. However, there is still a lack of information on its biology and few transcriptome studies are available. Our aim was to characterize the transcriptome of arapaima in order to shed light on molecular networks contributing to its unique traits. Through RNA-sequencing, we generated a transcriptome from eight tissues (brain, pituitary, heart, muscle, kidney, lung, ovary, and testis) collected from arapaima adults specimens. Using a genome-guided strategy associated with homologous protein evidence, 57,706 transcripts were assembled, which aligned to 23,353 high confidence protein-coding genes. The analysis revealed a global view of expression patterns, as well as it allowed us to identify tissue-specific gene clusters, transcription factors within the clusters, and to compare expression patterns between male and female. These analyses has generated tissue-specific and sex-biased transcriptome profiles, which will be helpful to understand its molecular biology, evolution, and also guide future functional studies of the arapaima.

genomics↗

bioRxiv2019

Chemical screening pipeline for identification of specific plant autophagy modulators

Autophagy is a major catabolic process in eukaryotes with a key role in homeostasis, programmed cell death and aging. In plants, autophagy is also known to regulate agriculturally important traits such as stress resistance, longevity, vegetative biomass and seed yield. Despite its significance, there is still a shortage of reliable tools modulating plant autophagy. Here we describe the first robust pipeline for identification of specific plant autophagy-modulating compounds. Our screening protocol comprises four phases: (i) high-throughput screening of chemical compounds in cell cultures of Nicotiana tabacum; (ii) confirmation of the identified hits in planta using Arabidopsis thaliana; (iii) further characterization of the effect using conventional molecular biology methods; (iv) verification of chemical specificity on autophagy in planta. The methods detailed here streamline identification of specific plant autophagy modulators and aid in unravelling the molecular mechanisms of plant autophagy.

plant biology↗

bioRxiv2020

Molecular and functional characterization of buffalo nasal epithelial odorant binding proteins and their structural insights by in-silico and biochemical approach

The olfactory system is capable of detecting and distinguishing thousands of environmental odorants that play a key role in reproduction, social behaviours including pheromones influenced classical events. Membrane secretary odorant binding proteins (OBPs) are soluble lipocalins, localized in the nasal membrane of mammals. They bind and carry odorants within the nasal epithelium to putative olfactory transmembrane receptors (ORs). While the existence of OBPs and their significant functions are very well known in insects and laboratory mammals, there is little information about the species-specific OBPs in buffaloes. In fact, the OBP of nasal epithelium has not yet been exploited to develop a suitable technique to detect estrus which is being reported as a difficult task in buffalo. In the present study, using molecular biology and protein engineering approaches, we have cloned six novel OBP isoforms from buffalo nasal epithelium (bnOBPs). Furthermore, 3D model was developed and molecular-docking, dynamics experiments were performed by In-silico approach. In particular, we found four residues (Phe104, Phe134, Phe69 and Asn118) from OBP1a, which had strong binding affinities towards two sex pheromones, specifically oleic acid and p-cresol. We expressed this protein in Escherichia coli to examine its involvement in the sex pheromone perception from female buffalo urine and validated through fluorescence quenching studies. Interestingly, fluorescence binding experiments also showed similar strong binding affinities of OBP1a to oleic acid and p-cresol. By using structural data, the binding specificity is also verified by site-directed mutagenesis of the four residues followed by in-vitro binding assays. Our results enable to better understand the functions of different nasal epithelium OBPs in buffaloes. They also lead to improved understanding of the interaction between olfactory proteins and odorants to develop highly selective biosensing devices for non-invasive detection of estrus in buffaloes.

bioinformatics↗

bioRxiv2022

Mouse lemur transcriptomic atlas elucidates primate genes, physiology, disease, and evolution

Mouse lemurs (Microcebus spp.) are an emerging primate model organism. However, little is known about their genetics or cellular and molecular biology. In the accompanying paper, we used large-scale single cell RNA-sequencing of 27 organs and tissues to identify over 750 molecular cell types, characterize their full transcriptomic profiles, and study evolution of primate cell types. Here we use the atlas to characterize mouse lemur genes, mutations, physiology, and disease. We uncover thousands of previously unidentified lemur genes and hundreds of thousands of new splice junctions that globally define lemur gene structures and reveal over 85,000 primate splice junctions missing in mice. We systematically explore the lemur immune system, comparing the global expression profiles of key immune genes in health and disease, and molecular mapping of immune cell development, trafficking, and their local and global activation to infection. We characterize primate/lemur-specific physiology and disease including molecular features of the immune program, of lemur adipocytes that exhibit dramatic seasonal rhythms, and of metastatic endometrial cancer that resembles the human malignancy. We identify and describe the expression patterns of over 400 primate genes missing in mice, many with similar expression patterns in human and lemur and some implicated in human disease. Finally, we provide an experimental framework for reverse genetic analysis by identifying naturally-occurring nonsense (null) mutations in three primate genes missing in mice and analyzing their transcriptional phenotypes. This work establishes mouse lemur as a tractable primate model organism for genetic and molecular analysis, and it prioritizes primate genes, splice junctions, physiology, and disease for future study.

genetics↗

bioRxiv2021

The Marburg Collection: A Golden Gate DNA Assembly Framework for Synthetic Biology Applications in Vibrio natriegens

Vibrio natriegens is known as the worlds fastest growing organism with a doubling time of less than 10 minutes. This incredible growth speed empowers V. natriegens as a chassis for synthetic and molecular biology, potentially replacing E. coli in many applications. While first genetic parts have been built and tested for V. natriegens, a comprehensive toolkit containing well-characterized and standardized parts did not exist. To close this gap, we created the Marburg Collection - a highly flexible Golden Gate Assembly-based cloning toolbox optimized for the emerging chassis organism V. natriegens. The Marburg Collection overcomes the paradigm of plasmid construction - integrating inserts into a backbone - by enabling the de novo assembly of plasmids from basic genetic parts. This allows users to select the plasmid replication origin and resistance part independently, which is highly advantageous when limited knowledge about the behavior of those parts in the target organism is available. Additional design highlights of the Marburg Collection are novel connector parts, which facilitate modular circuit assembly and, optionally, the inversion of individual transcription units to reduce transcriptional crosstalk in multigene constructs. To quantitatively characterize the genetic parts contained in the Marburg Collection in V. natriegens, we developed a reliable microplate reader measurement workflow for reporter experiments and overcame organismspecific challenges. We think the Marburg Collection with its thoroughly characterized parts will provide a valuable resource for the growing V. natriegens community.

synthetic biology↗

bioRxiv2017

An Inference Approach Combines Spatial And Temporal Gene Expression Data To Predict Gene Regulatory Networks In Arabidopsis Stem Cells

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is key for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. For this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network (GRN) inference algorithm that combines clustering with Dynamic Bayesian Network (DBN) inference. We leveraged the topology of our networks to infer potential key regulators. The results presented in this work show that our combination of molecular biology approaches, computational biology and mathematical modeling was key to identify candidate factors that function in the stem cells. Specifically, through experimental validation and mathematical modeling, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center (QC) function.

plant biology↗

bioRxiv2021

Towards a systematic characterization of protein complex function: a natural language processing and machine-learning framework

It is a general assumption of molecular biology that the ensemble of expressed molecules, their activities and interactions determine biological processes, cellular states and phenotypes. Quantitative abundance of transcripts, proteins and metabolites are now routinely measured with considerable depth via an array of "OMICS" technologies, and recently a number of methods have also been introduced for the parallel analysis of the abundance, subunit composition and cell state specific changes of protein complexes. In comparison to the measurement of the molecular entities in a cell, the determination of their function remains experimentally challenging and labor-intensive. This holds particularly true for determining the function of protein complexes, which constitute the core functional assemblies of the cell. Therefore, the tremendous progress in multi-layer molecular profiling has been slow to translate into increased functional understanding of biological processes, cellular states and phenotypes. In this study we describe PCfun, a computational framework for the systematic annotation of protein complex function using Gene Ontology (GO) terms. This work is built upon the use of word embedding-- natural language text embedded into continuous vector space that preserves semantic relationships-- generated from the machine reading of 1 million open access PubMed Central articles. PCfun leverages the embedding for rapid annotation of protein complex function by integrating two approaches: (1) an unsupervised approach that obtains the nearest neighbor (NN) GO term word vectors for a protein complex query vector, and (2) a supervised approach using Random Forest (RF) models trained specifically for recovering the GO terms of protein complex queries described in the CORUM protein complex database. PCfun consolidates both approaches by performing the statistical test for the enrichment of the top NN GO terms within the child terms of the predicted GO terms by RF models. Thus, PCfun amalgamates information learned from the gold-standard protein-complex database, CORUM, with the unbiased predictions obtained directly from the word embedding, thereby enabling PCfun to identify the potential functions of putative protein complexes. The documentation and examples of the PCfun package are available at https://github.com/sharmavaruns/PCfun. We anticipate that PCfun will serve as a useful tool and novel paradigm for the large-scale characterization of protein complex function.

bioinformatics↗

bioRxiv2019

Chromatin structure changes in Daphnia populations upon exposure to environmental cues - or - The discovery of Wolterecks \"Matrix\"

Phenotypic plasticity is an important feature of biological systems that is likely to play a major role in the future adaptation of organisms to the ongoing global changes. It may allow an organism to produce alternative phenotypes in responses to environmental cues. Modifications in the phenotype can be reversible but are sometimes enduring and can even span over generations. The notion of phenotypic plasticity was conceptualized in the early 20th century by Richard Woltereck. He introduced the idea that the combined relations of a phenotypic character and all environmental gradients that influence on it can be defined as \"norm of reaction\". Norms of reaction are specific to species and to lineages within species, and they are heritable. He postulated that reaction norms can progressively be shifted over generations depending on the environmental conditions. One of his biological models was the water-flee daphnia. Woltereck proposed that enduring phenotypic modifications and gene mutations could have similar adaptive effects, and he postulated that their molecular bases would be different. Mutations occurred in genes, while enduring modifications were based on something he called the Matrix. He suggested that this matrix (i) was associated with the chromosomes, (ii) that it was heritable, (iii) it changed during development of the organisms, and (iv) that changes of the matrix could be simple chemical substitutions of an unknown, but probably polymeric molecule. We reasoned that the chromatin has all postulated features of this matrix and revisited Wolterecks classical experiments with daphnia. We developed a robust and rapid ATAC-seq technique that allows for analyzing chromatin of individual daphnia and show here (i) that this technique can be used with minimal expertise in molecular biology, and (ii) we used it to identify open chromatin structure in daphnia exposed to different environmental cues. Our result indicates that chromatin structure changes consistently in daphnia upon this exposure confirming Wolterecks classical postulate.

evolutionary biology↗

bioRxiv2026

Linker-Length Landscape Mapping Enables Coupling of Diverse Synthetic Chemically Induced Dimerization Systems to Molecular Readouts

Programmable molecular biology increasingly requires strategies for converting engineered recognition or proximity modules into measurable outputs, particularly within transcriptional regulation, RNA imaging, and CRISPR-associated systems. Synthetic chemically induced dimerization (CID) systems provide a class of programmable recognition modules for such applications, yet generalized strategies for coupling structurally diverse CIDs to functional readouts remain limited. Here, we introduce a CID-to-output conversion strategy based on engineering of the linker-mediated coupling interface. Using single-fluorescent-protein sensors as an experimentally tractable optical model readout, we systematically varied paired N- and C-terminal linkers flanking circularly permuted green fluorescent protein (cpGFP) to map coupling landscapes across synthetic CID systems derived from combinatorial selection and computational protein design. The results revealed strong non-additive interactions across paired linkers and suggest that linker length is a first-order determinant of CID-to-output coupling. Across nanobody-, monobody-, and de novo-designed CID architectures, this framework yielded functional sensors with dynamic ranges up to 1270% and robust responses in mammalian cells. Together, this work demonstrates that effective CID-to-output conversion can be achieved by empirically mapping the linker-mediated coupling interface, providing a practical route for adapting synthetic CID to diverse programmable molecular readouts and nucleic-acid-associated synthetic biology systems O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/735888v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1ecc594org.highwire.dtl.DTLVardef@19fb822org.highwire.dtl.DTLVardef@f1e2ddorg.highwire.dtl.DTLVardef@653131_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2017

Key Issues Review: Evolution on rugged adaptive landscapes

Adaptive landscapes represent a mapping between genotype and fitness. Rugged adaptive landscapes contain two or more adaptive peaks: allele combinations that differ in two or more genes and confer higher fitness than intermediate combinations. How would a population evolve on such rugged landscapes? Evolutionary biologists have struggled with this question since it was first introduced in the 1930s by Sewall Wright.\n\nDiscoveries in the fields of genetics and biochemistry inspired various mathematical models of adaptive landscapes. The development of landscape models led to numerous theoretical studies analyzing evolution on rugged landscapes under different biological conditions. The large body of theoretical work suggests that adaptive landscapes are major determinants of the progress and outcome of evolutionary processes.\n\nRecent technological advances in molecular biology and microbiology allow experimenters to measure adaptive values of large sets of allele combinations and construct empirical adaptive landscapes for the first time. Such empirical landscapes have already been generated in bacteria, yeast, viruses, and fungi, and are contributing to new insights about evolution on adaptive landscapes.\n\nIn this Key Issues Review we will: (i) introduce the concept of adaptive landscapes; (ii) review the major theoretical studies of evolution on rugged landscapes; (iii) review some of the recently obtained empirical adaptive landscapes; (iv) discuss recent mathematical and statistical analyses motivated by empirical adaptive landscapes, as well as provide the reader with source code and instructions to implement simulations of adaptive landscapes; and (v) discuss possible future directions for this exciting field.

evolutionary biology↗