Biology subjects

Petersen, S. D.

Publications and source records attributed to Petersen, S. D..

8 recordsLinked to original sources

bioRxiv2024

StreptoCAD: An open-source software toolbox automating genome engineering workflows in streptomycetes

Streptomycetes hold immense potential for discovering novel bioactive molecules for applications in medicine or sustainable agriculture. However, high-throughput exploration is hampered by the current Streptomyces genetic engineering methods that involve the manual design of complex experimental molecular biological engineering strategies for each targeted gene. Here, we introduce StreptoCAD, an open-source software toolbox that automates and streamlines the design of genome engineering strategies in Streptomyces, supporting various CRISPR-based and gene overexpression methods. Once initiated, StreptoCAD designs all necessary DNA primers and CRISPR guide sequences, simulates plasmid assemblies (cloning) and the resulting modification of the genomic target(s), and further summarizes the information needed for laboratory implementation and documentation. StreptoCAD currently offers six design workflows, including the construction of overexpression libraries, base-editing, including multiplexed CRISPR-BEST plasmid generation, and genome engineering using CRISPR-Cas9, CRISPR-Cas3, and CRISPRi systems. In addition to automating the design process, StreptoCAD further secures compliance with the FAIR principles, ensuring reproducibility and ease of data management via standardized output files. To experimentally demonstrate the design process and output of StreptoCAD, we designed and constructed a series of gene overexpression strains in Streptomyces Go40/10, underscoring the tools efficiency and user-friendliness. This tool simplifies complex genetic engineering tasks and promotes collaboration through standardized workflows and design parameters. StreptoCAD is set to transform genome engineering in Streptomyces, making sophisticated genetic manipulations accessible for all and accelerating natural product discovery. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/629370v1_ufig1.gif" ALT="Figure 1000"> View larger version (56K): org.highwire.dtl.DTLVardef@42a7deorg.highwire.dtl.DTLVardef@1aef57org.highwire.dtl.DTLVardef@574e59org.highwire.dtl.DTLVardef@1d8dd3d_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Unraveling the genetic legacy of commercial whaling in bowhead whales and narwhals

Commercial whaling decimated many whale populations over several centuries. Bowhead whales (Balaena mysticetus) and narwhal (Monodon monoceros) have similar habitat requirements and are often seen together in the Canadian Arctic. Although their ranges overlap extensively, bowhead whales experienced significantly greater whaling pressure than narwhals. The different harvest histories but similar habitat requirements of these two species provide an opportunity to examine the demographic and genetic consequences of commercial whaling. We whole-genome resequenced Canadian Arctic bowhead whales and narwhals to delineate population structure and reconstruct demographic history. Bowhead whale effective population size sharply declined contemporaneously with the intense commercial whaling period. Narwhals instead exhibited recent growth in effective population size, reflecting limited opportunistic commercial harvest. Although the genetic diversity of bowhead whales and narwhals was similar, bowhead whales had more genetic diversity prior to commercial whaling and will likely continue to experience significant genetic drift in the future. In contrast, narwhals appear to have had long-term low genetic diversity and may not be at imminent risk of the consequences of the erosion of genetic diversity. This work highlights the importance of considering population trajectories in addition to genetic diversity when assessing the genetics of populations for conservation and management purposes.

genomics↗

bioRxiv2023

Climate change introduces threatened killer whale populations and conservation challenges to the Arctic

The Arctic is the fastest-warming region on the planet, and sea ice loss has opened new habitat for sub-Arctic species such as the killer whale (Orcinus orca). As apex predators, killer whales can cause significant ecosystem-scale changes, however, we know very little about killer whales in the Arctic. Setting conservation priorities for killer whales and their Arctic prey species requires knowledge of their evolutionary history and demography. We found that there are two highly genetically distinct, non-interbreeding populations of killer whales using the eastern Canadian Arctic--one population is newly identified as globally distinct. The effective sizes of both populations recently declined, and both are vulnerable to inbreeding and reduced adaptive potential. Furthermore, we present evidence that human-caused mortalities, particularly ongoing harvest, pose an ongoing threat to these populations. The certainty of substantial environmental change in the Arctic complicates conservation and management significantly. Killer whales bring top-down pressure to Arctic food webs, however, they also merit conservation concern. The opening of the Arctic to killer whales exemplifies the magnitude of complex decisions surrounding local peoples, wildlife conservation, and resource management as the effects of climate change are realized.

genomics↗

bioRxiv2023

Literate programming for iterative design-build-test-learn cycles in bioengineering

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of complex biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of a metabolic pathway designs for production of a key precursor to medicinal alkaloids. The teemi platform is publicly available at PyPi and GitHub.

bioinformatics↗

bioRxiv2021

HSP70-binding motifs function as protein quality control degrons

Protein quality control (PQC) degrons are short protein segments that target misfolded proteins for proteasomal degradation, and thus protect cells against the accumulation of potentially toxic non-native proteins. Studies have shown that PQC degrons are hydrophobic and rarely contain negatively charged residues, features which are shared with chaperone-binding regions. Here we explore the notion that chaperone-binding regions may function as PQC degrons. When directly tested, we found that a canonical Hsp70-binding motif (the APPY peptide) functioned as a dose-dependent PQC degron both in yeast and in human cells. In yeast, Hsp70, Hsp110, Fes1, and the E3 Ubr1 target the APPY degron. Screening revealed that the sequence space within the chaperone-binding region of APPY that is compatible with degron function is vast. We find that the number of exposed Hsp70-binding sites in the yeast proteome correlates with a reduced protein abundance and half-life. Our results suggest that when protein folding fails, chaperone-binding sites may operate as PQC degrons, and PQC-linked degradation therefore overlaps in specificity with chaperone binding. This sheds new light on how the PQC system has evolved to exploit the intrinsic capacity of chaperones to recognize misfolded proteins, thereby placing them at the nexus of protein folding and degradation. Significance StatementIt is broadly accepted that misfolded proteins are often rapidly degraded by the ubiquitin-proteasome system, but how cells specifically recognize this immensely diverse group of proteins is largely unknown. Here we show that upon uncoupling of protein folding from protein degradation, a canonical chaperone-binding motif doubles as a degradation signal (degron), and that within the context of a Hsp70-binding region, many sequences are compatible with degron function. We find that degradation is correlated with the number of Hsp70-binding sites within a protein, and that the number of exposed Hsp70-binding sites in the yeast proteome correlates with more rapid degradation.

biochemistry↗

bioRxiv2020

Evidence for an extreme founding effect in a highly successful invasive species

The adaptive potential of invasive species is thought to decrease during founding events due to reduced genetic diversity, limiting the new populations ability to colonize novel habitats. Barbary ground squirrels (Atlantoxerus getulus) were purportedly introduced as a single breeding pair to the island of Fuerteventura but have expanded to over a million individuals spread across the island in just over 50 years. We estimated the number of founders and measured the level of genetic diversity in this population using the mitochondrial displacement loop and microsatellite markers. Island samples (n = 19) showed no variation in the d-loop, suggesting a single founding female, while Moroccan samples (n = 6) each had unique mitochondrial haplotypes. The microsatellite data of the island population (n = 256 individuals) revealed a small effective population size, low levels of heterozygosity, and high levels of inbreeding, supporting a founding population size of two to three individuals. Our results suggest that A. getulus has undergone an intense genetic bottleneck during their colonization of the island. They are one of the few species where introduction effort does not explain invasion success, although further investigation may explain how they have avoided the worst expected effects following an extreme genetic bottleneck.

evolutionary biology↗

bioRxiv2019

Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models

In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can complement each other and be used in a combined approach to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets and produce a large combinatorial library of metabolic pathway designs with different promoters which, once phenotyped, provide the basis for machine learning algorithms to be trained and used for new design recommendations. The approach enables successful forward engineering of aromatic amino acid metabolism in yeast, with the new recommended designs improving tryptophan production by up to 17% compared to the best designs used for algorithm training, and ultimately producing a total increase of 106% in tryptophan accumulation compared to optimized reference designs. Based on a single high-throughput data-generation iteration, this study highlights the power of combining mechanistic and machine learning models to enhance their predictive power and effectively direct metabolic engineering efforts.

bioengineering↗

bioRxiv2019

Bayesian abundance estimation from genetic mark-recapture data when not all sites are sampled: an example with the bowhead whale

Estimating abundance is one of the most fundamental and important aspects of population biology, with major implications on how the status of a population is perceived and thus on conservation and management efforts. Although typically based on one of two methods (distance sampling or mark-recapture), there are many individual identification methods that can be used for mark-recapture purposes. In recent years, the use of genetic data for individual identification and abundance estimation through mark-recapture analyses have increased, and in some situations such genetic identifications are more efficient than their field-based counterparts for population monitoring. One issue with mark-recapture analyses, regardless of which method of individual identification is used, is that the study area must provide adequate opportunities for "capturing" all individuals within a population. However, many populations are unevenly and widely distributed, making it unfeasible to adequately sample all necessary areas. Here we develop an analytical technique that accounts for unsampled locations, and provides a means to infer "missing" individuals from unsampled locations, and therefore obtain more accurate abundance estimates when it is not possible to sample all sites. This method is validated using simulations, and is used to estimate abundance of the Eastern Canada-West Greenland (EC-WG) bowhead whale population. Based on these analyses, the estimated size of this population is 9,089 individuals, with a 95% highest density interval of 5,107-17,079.

zoology↗