Nominating novel proteins for anxiety via integrating human brain proteomes and genome-wide association study.

BACKGROUND: The underlying pathogenesis of anxiety remain elusive, making the pinpointing of potential therapeutic and diagnostic biomarkers for anxiety paramount to its efficient treatment. METHODS: We undertook a proteome-wide association study (PWAS), fusing human brain proteomes from both discovery (ROS/MAP; N = 376) and validation cohorts (Banner; N = 152) with anxiety genome-wide association study (GWAS) summary statistics. Complementing this, we executed transcriptome-wide association studies (TWAS) leveraging human brain transcriptomic data from the Common Mind Consortium (CMC) to discern the confluence of genetic influences spanning both proteomic and transcriptomic levels. We further scrutinized significant genes through a suite of methodologies. RESULTS: We discerned 14 genes instrumental in the genesis of anxiety through their specific cis-regulated brain protein abundance. Out of these, 6 were corroborated in the confirmatory PWAS, with 4 also showing associations with anxiety via their cis-regulated brain mRNA levels. A heightened confidence level was attributed to 5 genes (RAB27B, CCDC92, BTN2A1, TMEM106B, and DOC2A), taking into account corroborative evidence from both the confirmatory PWAS and TWAS, coupled with insights from mendelian randomization analysis and colocalization evaluations. A majority of the identified genes manifest in brain regions intricately linked to anxiety and predominantly partake in lysosomal metabolic processes. LIMITATIONS: The limited scope of the brain proteome reference datasets, stemming from a relatively modest sample size, potentially curtails our grasp on the entire gamut of genetic effects. CONCLUSION: The genes pinpointed in our research present a promising groundwork for crafting therapeutic interventions and diagnostic tools for anxiety.

Proteome partitioning constraints in long-term laboratory evolution.

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters. Here, we ask whether this same framework, operating at a level between genotype and fitness, informs physiological changes that occur on evolutionary timescales. Using a strain adapted to growth in glucose minimal medium, we find that the proteome is substantially remodeled over 40 000 generations. The most striking change is an apparent increase in enzyme efficiency, particularly in the enzymes of lower-glycolysis. We propose that deletion of metabolic flux-sensing regulation early in the adaptation results in increased enzyme saturation and can account for the observed proteome remodeling.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast.

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Yak genome database: a multi-omics analysis platform.

BACKGROUND: The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION: The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION: This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Integrated Transcriptome and Proteome Analysis Reveals the Regulatory Mechanism of Root Growth by Protein Disulfide Isomerase in Arabidopsis.

Protein disulfide isomerase (PDI, EC 5.3.4.1) is a thiol-disulfide oxidoreductase that plays a crucial role in catalyzing the oxidation and rearrangement of disulfides in substrate proteins. In plants, PDI is primarily involved in regulating seed germination and development, facilitating the oxidative folding of storage proteins in the endosperm, and also contributing to the formation of pollen. However, the role of PDI in root growth has not been previously studied. This research investigated the impact of PDI gene deficiency in plants by using 16F16 [2-(2-Chloroacetyl)-2,3,4,9-tetrahydro-1-methyl-1H-pyrido[3,4-b]indole-1-carboxylic acid methyl ester], a small-molecule inhibitor of PDI, to remove functional redundancy. The results showed that the growth of Arabidopsis roots was significantly inhibited when treated with 16F16. To further investigate the effects of 16F16 treatment, we conducted expression profiling of treated roots using RNA sequencing and a Tandem Mass Tag (TMT)-based quantitative proteomics approach at both the transcriptomic and proteomic levels. Our analysis revealed 994 differentially expressed genes (DEGs) at the transcript level, which were predominantly enriched in pathways associated with "phenylpropane biosynthesis", "plant hormone signal transduction", "plant-pathogen interaction" and "starch and sucrose metabolism" pathways. Additionally, we identified 120 differentially expressed proteins (DEPs) at the protein level. These proteins were mainly enriched in pathways such as "phenylpropanoid biosynthesis", "photosynthesis", "biosynthesis of various plant secondary metabolites", and "biosynthesis of secondary metabolites" pathways. The comprehensive transcriptome and proteome analyses revealed a regulatory network for root shortening in Arabidopsis seedlings under 16F16 treatment, mainly involving phenylpropane biosynthesis and plant hormone signal transduction pathways. This study enhances our understanding of the significant role of PDIs in Arabidopsis root growth and provides insights into the regulatory mechanisms of root shortening following 16F16 treatment.

TOPMed imputed genomics enhances genomic atlas of the human proteome in brain, cerebrospinal fluid, and plasma.

Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community.

Proteogenomic Gene Structure Validation in the Pineapple Genome.

MD2 pineapple (Ananas comosus) is the second most important tropical crop that preserves crassulacean acid metabolism (CAM), which has high water-use efficiency and is fast becoming the most consumed fresh fruit worldwide. Despite the significance of environmental efficiency and popularity, until very recently, its genome sequence has not been determined and a high-quality annotated proteome has not been available. Here, we have undertaken a pilot proteogenomic study, analyzing the proteome of MD2 pineapple leaves using liquid chromatography-mass spectrometry (LC-MS/MS), which validates 1781 predicted proteins in the annotated F153 (V3) genome. In addition, a further 603 peptide identifications are found that map exclusively to an independent MD2 transcriptome-derived database but are not found in the standard F153 (V3) annotated proteome. Peptide identifications derived from these MD2 transcripts are also cross-referenced to a more recent and complete MD2 genome annotation, resulting in 402 nonoverlapping peptides, which in turn support 30 high-quality gene candidates novel to both pineapple genomes. Many of the validated F153 (V3) genes are also supported by an independent proteomics data set collected for an ornamental pineapple variety. The contigs and peptides have been mapped to the current F153 genome build and are available as bed files to display a custom gene track on the Ensembl Plants region viewer. These analyses add to the knowledge of experimentally validated pineapple genes and demonstrate the utility of transcript-derived proteomics to discover both novel genes and genetic structure in a plant genome, adding value to its annotation.

Freshwater genome-reduced bacteria exhibit pervasive episodes of adaptive stasis.

The emergence of bacterial species is rooted in their inherent potential for continuous evolution and adaptation to an ever-changing ecological landscape. The adaptive capacity of most species frequently resides within the repertoire of genes encoding the secreted proteome (SP), as it serves as a primary interface used to regulate survival/reproduction strategies. Here, by applying evolutionary genomics approaches to metagenomics data, we show that abundant freshwater bacteria exhibit biphasic adaptation states linked to the eco-evolutionary processes governing their genome sizes. While species with average to large genomes adhere to the dominant paradigm of evolution through niche adaptation by reducing the evolutionary pressure on their SPs (via the augmentation of functionally redundant genes that buffer mutational fitness loss) and increasing the phylogenetic distance of recombination events, most of the genome-reduced species exhibit a nonconforming state. In contrast, their SPs reflect a combination of low functional redundancy and high selection pressure, resulting in significantly higher levels of conservation and invariance. Our findings indicate that although niche adaptation is the principal mechanism driving speciation, freshwater genome-reduced bacteria often experience extended periods of adaptive stasis. Understanding the adaptive state of microbial species will lead to a better comprehension of their spatiotemporal dynamics, biogeography, and resilience to global change.

Evolutionary analyses of intrinsically disordered regions reveal widespread signals of conservation.

Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common "evolutionary signatures," i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.

AlphaFun: Structural-Alignment-Based Proteome Annotation Reveals why the Functionally Unknown Proteins (uPE1) Are So Understudied.

With the rapid expansion of sequencing of genomes, the functional annotation of proteins becomes a bottleneck in understanding proteomes. The Chromosome-centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome and find functional annotations for them. However, until now there are still 1137 identified human proteins without functional annotation, called uPE1 proteins. Sequence alignment was insufficient to predict their functions, and the crystal structures of most proteins were unavailable. In this study, we demonstrated a new functional annotation strategy, AlphaFun, based on structural alignment using deep-learning-predicted protein structures. Using this strategy, we functionally annotated 99% of the human proteome, including the uPE1 proteins and missing proteins, which have not been identified yet. The accuracy of the functional annotations was validated using the known-function proteins. The uPE1 proteins shared similar functions to the known-function PE1 proteins and tend to express only in very limited tissues. They are evolutionally young genes and thus should conduct functions only in specific tissues and conditions, limiting their occurrence in commonly studied biological models. Such functional annotations provide hints for functional investigations on the uPE1 proteins. This proteome-wide-scale functional annotation strategy is also applicable to any other species.

Nature as blueprint: Global phenotype engineering of CHO production cells based on a multi-omics comparison with plasma cells.

Especially for the production of artificial, difficult to express molecules a further development of the CHO production cell line is required to keep pace with the continuously increasing demands. However, the identification of novel targets for cell line engineering to improve CHO cells is a time and cost intensive process. Since plasma cells are evolutionary optimized for a high antibody expression in mammals, we performed a comprehensive multi-omics comparison between CHO and plasma cells to exploit optimized cellular production traits. Comparing the transcriptome, proteome, miRNome, surfaceome and secretome of both cell lines identified key differences including 392 potential overexpression targets for CHO cell engineering categorized in 15 functional classes like transcription factors, protein processing or secretory pathway. In addition, 3 protein classes including 209 potential knock-down/out targets for CHO engineering were determined likely to affect aggregation or proteolysis. For production phenotype engineering, several of these novel targets were successfully applied to transient and transposase mediated overexpression or knock-down strategies to efficiently improve productivity of CHO cells. Thus, substantial improvement of CHO productivity was achieved by taking nature as a blueprint for cell line engineering.

DESP demixes cell-state profiles from dynamic bulk molecular measurements.

Understanding the dynamic expression of proteins and other key molecules driving phenotypic remodeling in development and pathobiology has garnered widespread interest, yet the exploration of these systems at the foundational resolution of the underlying cell states has been significantly limited by technical constraints. Here, we present DESP, an algorithm designed to leverage independent estimates of cell-state proportions, such as from single-cell RNA sequencing, to resolve the relative contributions of cell states to bulk molecular measurements, most notably quantitative proteomics, recorded in parallel. We applied DESP to an in vitro model of the epithelial-to-mesenchymal transition and demonstrated its ability to accurately reconstruct cell-state signatures from bulk-level measurements of both the proteome and transcriptome, providing insights into transient regulatory mechanisms. DESP provides a generalizable computational framework for modeling the relationship between bulk and single-cell molecular measurements, enabling the study of proteomes and other molecular profiles at the cell-state level using established bulk-level workflows.

Phylogeny and Expansion of Serine/Threonine Kinases in Phagocytotic Bacteria in the Phylum Planctomycetota.

The recently isolated bacterium "Candidatus Uabimicrobium amorphum" is the only known prokaryote that can engulf other bacterial cells. Its proteome contains a high fraction of proteins involved in signal transduction systems, which is a feature normally associated with multicellularity in eukaryotes. Here, we present a protein-based phylogeny which shows that "Ca. Uabimicrobium amorphum" represents an early diverging lineage that clusters with the Saltatorellus clade within the phylum Planctomycetota. A gene flux analysis indicated a gain of 126 protein families for signal transduction functions in "Ca. Uabimicrobium amorphum", of which 66 families contained eukaryotic-like Serine/Threonine kinases with Pkinase domains. In total, we predicted 525 functional Serine/Threonine kinases in "Ca. Uabimicrobium amorphum", which represent 8% of the proteome and is the highest fraction of Serine/Threonine kinases in a bacterial proteome. The majority of Serine/Threonine kinases in this species are membrane proteins and 30% contain long, tandem arrays of WD40 or TPR domains. The pKinase domain was predicted to be located in the cytoplasm, while the WD40 and TPR domains were predicted to be located in the periplasm. Such domain combinations were also identified in the Serine/Threonine kinases of other species in the Planctomycetota, although in much lower abundances. A phylogenetic analysis of the Serine/Threonine kinases in the Planctomycetota inferred from the Pkinase domain alone provided support for lineage-specific expansions of the Serine/Threonine kinases in "Ca. Uabimicrobium amorphum". The results imply that expansions of eukaryotic-like signal transduction systems are not restricted to multicellular organisms, but have occurred in parallel in prokaryotes with predatory lifestyles and phagocytotic-like behaviors.

New plastids, old proteins: repeated endosymbiotic acquisitions in kareniacean dinoflagellates.

Dinoflagellates are a diverse group of ecologically significant micro-eukaryotes that can serve as a model system for plastid symbiogenesis due to their susceptibility to plastid loss and replacement via serial endosymbiosis. Kareniaceae harbor fucoxanthin-pigmented plastids instead of the ancestral peridinin-pigmented ones and support them with a diverse range of nucleus-encoded plastid-targeted proteins originating from the haptophyte endosymbiont, dinoflagellate host, and/or lateral gene transfers (LGT). Here, we present predicted plastid proteomes from seven distantly related kareniaceans in three genera (Karenia, Karlodinium, and Takayama) and analyze their evolutionary patterns using automated tree building and sorting. We project a relatively limited ( ~ 10%) haptophyte signal pointing towards a shared origin in the family Chrysochromulinaceae. Our data establish significant variations in the functional distributions of these signals, emphasizing the importance of micro-evolutionary processes in shaping the chimeric proteomes. Analysis of plastid genome sequences recontextualizes these results by a striking finding the extant kareniacean plastids are in fact not all of the same origin, as two of the studied species (Karlodinium armiger, Takayama helix) possess plastids from different haptophyte orders than the rest.

DnaK duplication and specialization in bacteria correlates with increased proteome complexity.

The chaperone 70 kDa heat shock protein (Hsp70) is important for cells from bacteria to humans to maintain proteostasis, and all eukaryotes and several prokaryotes encode Hsp70 paralogs. Although the mechanisms of Hsp70 function have been clearly illuminated, the function and evolution of Hsp70 paralogs is not well studied. DnaK is a highly conserved bacterial Hsp70 family. Here, we show that dnaK is present in 98.9% of bacterial genomes, and 6.4% of them possess two or more DnaK paralogs. We found that the duplication of dnaK is positively correlated with an increase in proteomic complexity (proteome size, number of domains). We identified the interactomes of the two DnaK paralogs of Myxococcus xanthus DK1622 (MxDnaKs), which revealed that they are mostly nonoverlapping, although both prefer α and ß domain proteins. Consistent with the entire M. xanthus proteome, MxDnaK substrates have both significantly more multi-domain proteins and a higher isoelectric point than that of Escherichia coli, which encodes a single DnaK homolog. MxDnaK1 is transcriptionally upregulated in response to heat shock and prefers to bind cytosolic proteins, while MxDnaK2 is downregulated by heat shock and is more associated with membrane proteins. Using domain swapping, we show that the nucleotide-binding domain and the substrate-binding ß domain are responsible for the significant differences in DnaK interactomes, and the nucleotide binding domain also determines the dimerization of MxDnaK2, but not MxDnaK1. Our work suggests that bacterial DnaK has been duplicated in order to deal with a more complex proteome, and that this allows evolution of distinct domains to deal with different subsets of target proteins.IMPORTANCEAll eukaryotic and ~40% of prokaryotic species encode multiple 70 kDa heat shock protein (Hsp70) homologs with similar but diversified functions. Here, we show that duplication of canonical Hsp70 (DnaK in prokaryotes) correlates with increasing proteomic complexity and evolution of particular regions of the protein. Using the Myxococcus xanthus DnaK duplicates as a case, we found that their substrate spectrums are mostly nonoverlapping, and are both consistent to that of Escherichia coli DnaK in structural and molecular characteristics, but show differential enrichment of membrane proteins. Domain/region swapping demonstrated that the nucleotide-binding domain and the ß substrate-binding domain (SBDß), but not the SBDα or disordered C-terminal tail region, are responsible for this functional divergence. This work provides the first direct evidence for regional evolution of DnaK paralogs.

ProTInSeq: transposon insertion tracking by ultra-deep DNA sequencing to identify translated large and small ORFs.

Identifying open reading frames (ORFs) being translated is not a trivial task. ProTInSeq is a technique designed to characterize proteomes by sequencing transposon insertions engineered to express a selection marker when they occur in-frame within a protein-coding gene. In the bacterium Mycoplasma pneumoniae, ProTInSeq identifies 83% of its annotated proteins, along with 5 proteins and 153 small ORF-encoded proteins (SEPs; ≤100 aa) that were not previously annotated. Moreover, ProTInSeq can be utilized for detecting translational noise, as well as for relative quantification and transmembrane topology estimation of fitness and non-essential proteins. By integrating various identification approaches, the number of initially annotated SEPs in this bacterium increases from 27 to 329, with a quarter of them predicted to possess antimicrobial potential. Herein, we describe a methodology complementary to Ribo-Seq and mass spectroscopy that can identify SEPs while providing other insights in a proteome with a flexible and cost-effective DNA ultra-deep sequencing approach.

Integration Analysis of Hair Follicle Transcriptome and Proteome Reveals the Mechanisms Regulating Wool Fiber Diameter in Angora Rabbits.

Fiber diameter is an important characteristic that determines the quality and economic value of rabbit wool. This study aimed to investigate the genetic determinants of wool fiber diameter through an integration analysis using transcriptomic and proteomic datasets from hair follicles of coarse and fine wool from Angora rabbits. Using a 4D label-free technique, we identified 423 differentially expressed proteins (DEPs) in hair follicles of coarse and fine wool in Angora rabbits. Eighteen DEPs were examined using parallel reaction monitoring, which verified the reliability of our proteomic data. Functional enrichment analysis revealed that a set of biological processes and signaling pathways related to wool growth and hair diameter were strongly enriched by DEPs with fold changes greater than two, such as keratinocyte differentiation, skin development, epidermal and epithelial cell differentiation, epidermis and epithelium development, keratinization, and estrogen signaling pathway. Association analysis and protein-protein interaction network analysis further showed that the keratin (KRT) family members, including KRT77, KRT82, KRT72, KRT32, and KRT10, as well as CASP14 and CDSN, might be key factors contributing to differences in fiber diameter. Our results identified DEPs in hair follicles of coarse and fine wool and promoted understanding of the molecular mechanisms underlying wool fiber diameter variation among Angora rabbits.

Semen proteome and transcriptome of the endangered black-footed ferret (Mustela nigripes) show association with the environment and fertility outcome.

The ex situ population of the endangered black-footed ferret (Mustela nigripes) has been experiencing declines in reproductive success over the past 30 years of human-managed care. A potential cause may be environmental-dependent inbreeding depression with diet being one of the contributing factors since ferrets are not fed their natural diet of prairie dogs. Here, we generated and analyzed semen proteome and transcriptome data from both wild and ex situ ferrets maintained on various diets. We identified 1757 proteins across all samples, with 149 proteins unique to the semen of wild ferrets and forming a ribosomal predicted protein-protein interaction cluster. Wild ferrets also differed from ex situ ferrets in their transcriptomic profile, showing enrichment in ribosomal RNA processing and potassium ion transport. Successful fertility outcomes documented for ex situ ferrets showed the strongest association with the semen transcriptome, with enrichment in genes involved in translation initiation and focal adhesion. Fertility also synergized with the effect of diet on differentially expressed transcriptomes, mainly affecting genes enriched in mitochondrial function. Our data and functional networks are important for understanding the causes and mechanisms of declining fertility in the ex situ ferret population and can be used as a resource for future conservation efforts.