Internal symmetry in protein structures: prevalence, functional relevance and evolution

Proteins have evolved to carry out very specific functions within the cell by interacting with a diverse set of biomolecules. Understanding how a protein's higher order structure relates to its function is important for defining the molecular basis of these interactions. In recent years, mass spectrometry has become an important tool for dissecting protein structure and function. Using electrospray ionization (ESI)- and matrix-assisted laser desorption/ionization (MALDI)-based approaches, it has been possible to monitor protein folding, characterize noncovalent protein complexes, and assess the contribution of individual amino acid residues to a protein's function. Here, it is our goal to summarize these approaches and highlight recent, biologically relevant applications where mass spectrometry has provided unique insight into the mysteries of protein structure and function.

Exposure to heavy metal-contaminated sediments disrupts gene expression, lipid profile, and life history traits in the midge Chironomus riparius

Responses to anthropogenic pollution may occur at various levels of biological organization from organelles to the ecosystem, over periods of time varying from seconds to years. Thus, it is no wonder that single explanations for the decline of forests have ranged from the biochemical to the biogeochemical, and from the microbiological to the ecological. Explaining an observed phenomenon depends on the level of organization immediately below the level of observation, but the significance of the observation lies in the level immediately above (Passioura 1979). Information about different levels of biological organization must be integrated if clearer understanding, rather than greater confusion, is to be achieved (Ashmore 1988). Thus, Ashmore (1988) has emphasized that quantitatively measuring selected tree components may fail to explain the ultimate course of a tree’s decline. Only when the whole organism’s vitality both aboveand belowground is assessed, and the significance of the results on the appropriate spatial and temporal scales evaluated, can a firm conclusion about the causes of decline be reached. These criteria also apply to assessing decline in whole forest ecosystems (Ulrich 1987).

The study of protein structure is of great interest in fields like biology, pharmacology and medicine due to the great impact that structural configuration has on protein functioning and behaviour. However, fully atomistic models are inaccurate or directly unavailable for many protein conformations because of the constraints that protein crystallography, the default method to obtain atomic configurations, imposes on protein structures. In that regard, Small Angle X-Ray Scattering (SAXS) has become a widely used tool to study proteins in solution, as it can retrieve structural information from proteins in their native environment without the need for crystallography, but at the cost of significant loss of information, and the need to interpret or reconstruct structure from the measurements. SAXS measurements consist of a band-pass filtered spherically averaged Fourier transform of the protein's atomic pair-distribution function, resulting in a 1D signal with limited support and with a restricted resolution range between 50 to 10 angstroms. Determining protein configurations from SAXS measurements is, thus, a very ill-posed challenge as only 1D information is available to reconstruct the protein's 3D structure and requiring regularized and constrained optimization frameworks to successfully solve it.

MotivationIn recent years, protein function prediction has broken through the bottleneck of sequence features, significantly improving prediction accuracy using high-precision protein structures predicted by AlphaFold2. While single-species protein function prediction methods have achieved remarkable success, multi-species approaches still face challenges such as difficulties in multi-source data integration and insufficient knowledge transfer between distantly-related species. How to integrate large-scale data and provide effective cross-species label propagation for species with sparse protein annotations remains a critical and unresolved challenge. To address this problem, we propose the MSNGO (Multi-species protein Structures and Network to predict GO terms) model, which integrates structural features and network propagation methods. Our validation shows that using structural features can significantly improve the accuracy of multi-species protein function prediction.ResultsWe employ graph representation learning techniques to extract amino acid representations from protein structure contact maps and train a structural model using a graph convolution pooling module to derive protein-level structural features. After incorporating the sequence features from ESM-2, we apply a network propagation algorithm to aggregate information and update node representations within a heterogeneous network. The results demonstrate that MSNGO outperforms previous multi-species protein function prediction methods that rely on sequence features and protein-protein networks.Availability and implementationhttps://github.com/blingbell/MSNGO.

Pseudomonas aeruginosa is a bacterium resistant to a large number of antibiotics and disinfectants. Since the antigens are responsible for producing this resistance, and most of these are proteins, the objective of this work was to predict by computational means the 3D structure and function of PA2481 protein, determining whether is involved in the antibiotic resistance of this bacterium. In order to do this, the primary structure was analyzed computationally by using servers PROSITE, PFAM, BLAST, PROTPARAM, GLOBPLOT, and PROTSCALE. The secondary structure was obtained by the consensus of algorithms SOPM, PREDATOR, DPM, DSC, and GOR4. The 3D structure was predicted with the I-TASSER server and its stereochemical conformation was evaluated with the STRUCTURE ASSESSMENT tool. The final model was visualized with PyMol program. As a result, the 3D structure of PA2481 is proposed according to its stereochemical conformation; two domains are identified as cytochrome c. The function of the protein may be related to electron transport and proton pumping to generate ATP in Pseudomonas aeruginosa. These results allow a better understanding of the role this protein plays in the physiology of this bacterium.Keywordshypothetical proteincystic fibrosisexternal otitisstructural modelingPA2481 Pseudomonas aeruginosa

Protein engineering, the process by which novel proteins with desired properties are developed, has grown by leaps and bounds since the first examples of protein mutagenesis were described over three decades ago. In the last 30 years, protein engineers have successfully created a wide range of proteins tailored to specific industrial, medical, and research applications. Yet challenges remain that prevent the engineering of complex protein functions on demand. With the aim of creating a forum for the protein engineering community, the inaugural Protein Engineering Canada Conference was held on June 20–22, 2014, in Ottawa, Canada. Over the course of the 2-day conference, 115 protein scientists from over 30 institutions representing 5 countries shared ideas, networked with colleagues, and learned about exciting new research covering a broad array of topics such as enzyme engineering, computational protein design, X-ray crystallography, protein NMR, molecular modeling, and protein evolution. This special issue highlights the breadth of research that was covered during the Protein Engineering Canada Conference by including previously unpublished research articles submitted by speakers as well as some selections that were submitted directly to Protein Science.

Cumin (Cuminum cyminum L.) belongs to Apiaceae family, is an important seed spice and one of the earliest spices used by mankind for its aromatic and medicinal properties. Cumin seeds are very commonly used to give flavour and texture to the food. In addition, it also acts as preservative and provides nutritional and health benefits. The typical aroma of the cumin seeds is due to their volatile oil content, the principal constituent of which is cuminol (cumin aldehyde). Studies have been done on properties of the essential oil content of cumin and other aspects. Only few studies are available citing the nucleotides sequences present in cumin but no reports are available on in-silico studies of proteins structure supposed to be present in cumin. In the present study, a high quality 3D structure and function of cumin protein (GQ 33) have been predicted for the hypothetical amino acid sequence obtained from reported nucleotides of cumin. The physiochemical properties for GQ 33 cumin protein were identified using Protparam. The instability index 39.52, isoelectric point (pI) 9.97 and grand average hydropathicity (GRAVY) -0.245 determined from primary and secondary structural analysis illustrate the stability of GQ 33 protein. Stability of 3D structure of protein was confirmed using Ramachandran plot having 95.7% residues or empirically distributed data-points present in the structure lie in most favoured region. For the prediction of secondary structure of protein FASTA sequences were used and prediction was performed using PSIPRED, JPRED, Protein Predict and SOPMA. SAVES server was used for further validation of protein structure.

BackgroundFlatfish live in a diverse marine ecosystem that is changing due to natural variations and anthropogenic influences. These changes can evoke a stress response mainly resulting in production of the glucocorticoid cortisol, which mediates effects on various levels of biological organization. The finding that cortisol accumulates in fish scales, offering a retrospective view on cortisol production, provides opportunities to use this matrix for chronic stress assessment. The present study is the first to gather information on scale cortisol concentration in wild-caught common dab (Limanda limanda), based on a two-pronged approach using (1) field measurements and (2) a laboratory in vivo-study where wild-caught dab were fed by cortisol-spiked feed during 30 or 90 days to demonstrate the possible accumulation of cortisol in the scales and to evaluate its impact on fish health.ResultsBased on the field measurements, the average scale cortisol concentration in wild-caught fish was 0.0034 ± 0.0046 µg kg−1 scale (n = 67). This indicates that wild common dab is indeed able to incorporate cortisol in the scales.Based on the experimental data, the cortisol-fed fish showed an increased plasma cortisol concentration (80.16 ± 82.58 µg L−1) compared to the control group (4.54 ± 9.57 µg L−1) after 30 days of cortisol feeding. The increase in plasma cortisol concentration was positively correlated with an increased cortisol concentration in the scale after 30 days of cortisol-spiked feeding. This correlation was, however, no longer observed after 90 days of cortisol-spiked feeding. Interestingly, cortisol concentration of the scales on the pigmented side was significantly higher compared to the non-pigmented side. Some health parameters such as epidermal thickness, body condition and Ichthyobodo sp. parasitic infection showed a correlation with scale cortisol concentration after 30 days.ConclusionsWe have demonstrated that common dab is able to accumulate cortisol in its scales. This seems to occur proportionally to circulating concentrations of plasma cortisol in fish fed with cortisol supplemented feed after 30 days.

Linking ecology and evolution can be challenging, particularly as these fields evolve rapidly tracking technological and theoretical developments. Thus, it is important for practitioners of different biological disciplines to understand new opportunities and challenges. Since theory and methods evolve, so will research programmes—often tracking opportunity. Here, we describe a research programme where we have investigated the population biology of grayling Thymallus thymallus in a Norwegian alpine landscape over three decades. Starting with classical ecological studies, we identified a set of populations that had evolved population-specific phenotypic traits over a relatively short time span (10–30 generations). These observations led us into evolutionary studies at various levels of biological organization, using population and quantitative genetic, transcriptomic and proteomic approaches. Overall, the results show that the populations exhibit evolutionary responses to local-scale differences in environment (mainly water temperature during early development). Further, plastic responses are important in the early phase of population diversification. Population genomic studies are now becoming possible following the completion of an annotated genome. This will help us and others in addressing questions about the genetic architecture of traits important for local adaptation, thus emphasizing that combining ecological and evolutionary approaches is more important and interesting than ever.

Effects of alternative connectivity on behavior of randomly constructed Boolean networks

BackgroundSince their introduction in 2009, the BioNLP Shared Task events have been instrumental in advancing the development of methods and resources for the automatic extraction of information from the biomedical literature. In this paper, we present the Cancer Genetics (CG) and Pathway Curation (PC) tasks, two event extraction tasks introduced in the BioNLP Shared Task 2013. The CG task focuses on cancer, emphasizing the extraction of physiological and pathological processes at various levels of biological organization, and the PC task targets reactions relevant to the development of biomolecular pathway models, defining its extraction targets on the basis of established pathway representations and ontologies.ResultsSix groups participated in the CG task and two groups in the PC task, together applying a wide range of extraction approaches including both established state-of-the-art systems and newly introduced extraction methods. The best-performing systems achieved F-scores of 55% on the CG task and 53% on the PC task, demonstrating a level of performance comparable to the best results achieved in similar previously proposed tasks.ConclusionsThe results indicate that existing event extraction technology can generalize to meet the novel challenges represented by the CG and PC task settings, suggesting that extraction methods are capable of supporting the construction of knowledge bases on the molecular mechanisms of cancer and the curation of biomolecular pathway models. The CG and PC tasks continue as open challenges for all interested parties, with data, tools and resources available from the shared task homepage.

Predator-prey interactions are a cornerstone of many ecological and evolutionary processes that influence various levels of biological organization, from individuals to ecosystems. Predators play a crucial role in shaping ecosystems through the consumption of prey species and non-consumptive effects. Non-consumptive effects (NCEs) can induce changes in prey behavior, including altered foraging strategies, habitat selection, life history and anti-predator responses. These defensive strategies have physiological consequences for prey, affecting their growth, reproduction and immune function to name a few. Numerous experimental studies have incorporated NCEs in investigating predator-prey dynamics in the past decade. Interestingly, predator-prey systems can also be used as experimental models to answer physiology, cognition and adaptability questions. In this Commentary, I highlight research that uses NCEs in predator-prey systems to provide novel insights into cognition, adaptation, epigenetic inheritance and aging. I discuss the evolution of instinct, anxiety and other cognitive disorders, the shaping of brain connectomes, stress-induced aging and the development of behavioral coping styles. I outline how studies can integrate the investigation of NCEs with advanced behavioral, genomic and neurological tools to provide novel insights into physiological and cognitive health.

Phenotypic plasticity can be broadly defined as the ability of one genotype to produce more than one phenotype when exposed to different environments, as the modification of developmental events by the environment, or as the ability of an individual organism to alter its phenotype in response to changes in environmental conditions. Not surprisingly, the study of phenotypic plasticity is innately interdisciplinary and encompasses aspects of behavior, development, ecology, evolution, genetics, genomics, and multiple physiological systems at various levels of biological organization. From an ecological and evolutionary perspective, phenotypic plasticity may be a powerful means of adaptation and dramatic examples of phenotypic plasticity include predator avoidance, insect wing polymorphisms, the timing of metamorphosis in amphibians, osmoregulation in fishes, and alternative reproductive tactics in male vertebrates. From a human health perspective, documented examples of plasticity most commonly include the results of exercise, training, and/or dieting on human morphology and physiology. Regardless of the discipline, phenotypic plasticity has increasingly become the target of a plethora of investigations with the methodological approaches utilized ranging from the molecular to whole organsimal. In this article, we provide a brief historical outlook on phenotypic plasticity; examine its potential adaptive significance; emphasize recent molecular approaches that provide novel insight into underlying mechanisms, and highlight examples in fishes and insects. Finally, we highlight examples of phenotypic plasticity from a human health perspective and underscore the use of mouse models as a powerful tool in understanding the genetic architecture of phenotypic plasticity. © 2012 American Physiological Society. Compr Physiol 2:1417‐1439, 2012.

Biomarkers are used to assess the biological impacts of contaminants on aquatic organisms. There are various levels of biological organization at which biomarkers can be employed, but identifying specific and sensitive biomarkers in a multicontaminated estuarine environment is challenging. Most of the biomarker studies in the Pearl River Estuary have focussed on the estuarine oyster Crassostrea hongkongensis. Measurements of biomarkers in these oysters have suggested that high bioavailabilities of trace metals in the Pearl River Estuary are causing detectable ecotoxicological effects on the estuarine oysters at various biological levels such as the biochemical and physiological levels, the latter manifested in deleterious reproductive effects. Revealing the impacts of contaminants other than trace metals in the estuarine biota will be particularly relevant in future studies.