Fructose-containing sugars are a focus of attention as a public health target for their putative role in obesity and cardiometabolic disease including diabetes. The fructose moiety is singled out to be the primary driver for the harms of sugars due to its unique endocrine signal and pathophysiological role. However, this is only supported by ecological studies, animal models of overfeeding and select human intervention studies with supraphysiological doses or lack of control for energy. The highest level of evidence from systematic reviews and meta-analyses of controlled trials has not shown that fructose-containing sugars behave any differently from other forms of digestible carbohydrates. Fructose-containing sugars can only lead to weight gain and other unintended harms on cardiometabolic risk factors insofar as the excess calories they provide. Prospective cohort studies, which provide the strongest observational evidence, have shown an association between fructose-containing sugars and cardiometabolic risk including weight gain, cardiovascular disease outcomes and diabetes only when restricted to sugar-sweetened beverages and not for sugars from other sources. In fact, sugar-sweetened beverages are a marker of an unhealthy lifestyle and their drinkers consume more calories, exercise less, smoke more and have a poor dietary pattern. The potential for overconsumption of sugars in the form of sugary foods and drinks makes targeting sugars, as a source of excess calories, a prudent strategy. However, sugar content should not be the sole determinant of a healthy diet. There are many other factors in the diet—some providing excess calories while others provide beneficial nutrients. Rather than just focusing on one energy source, we should consider the whole diet for health benefits. Overconsumption of dietary sugars with their potential to cause cardiometabolic disease has emerged as an important public health issue, highlighted by the vast coverage given in academic journals and the popular press. Special focus is on the fructose moiety within sugars due to the former’s unique metabolic and endocrine response. Fructose-containing sugars that are ‘added’ to our diets are alleged to be an important risk factor for the development of obesity , cardiomThe story of dietary sugars and their potential harms on our health has oscillated several times over the past five decades as more scientific evidence on this topic came to light. Hence, it is important to give a brief historical background to the scientific controversy surrounding dietary sugars. The sugar debate first started in the 1970s when opposite positions were presented as explanations for the epidemic of cardiovascular disease. In the 1970, the American biochemist Ancel Keys, using his seven countries ecological study, argued for a role of saturated fat in heart disease . At thatDietary sugars came into forefront again in 2004 when Dr. George Bray, an eminent obesity researcher, published an ecological study that showed a parallel rise between overweight/obesity and fructose-containing sugars in the USA . In an eDr. Bray’s study sparked a real interest in this field and kick-started a new sugar debate that has continued fiercely to this day. Dr. Robert Lustig, a paediatrician from University of California San Francisco, in 2009 made a passionate case against fructose in the popular YouTube video, ‘Sugar: The bitter truth’  that curAt first glance, the case presented against sugars is quite persuasive, which hinges on implicating the fructose moiety for its unique metabolic and endocrine responses. Fructose is present in all main dietary sugars except for milk. Proponents of this fructose-centric view present ecological data, supporting it with animal studies and human mechanistic studies that show adverse effects of fructose in very high doses . This evIt is worth noting that the bulk of the biochemical and metabolic evidence presented against fructose is based on rodent models , 30, 34 Several international and national health authorities have recently changed their dietary guidelines recommending a restriction in dietary sugars intake. Is this recommendation based on evidence of harm in relation to obesity, diabetes and cardiovascular disease? A careful review of these guidelines reveals that most of these guidelines use evidence from dental harms and caloric harms associated with excess sugar, especially SSB intake. The WHO recommended added sugars to be <10% of total daily energy intake based on observational data from dental caries . This amDietary sugars intake has become a charged and emotive issue, both academically and in the media, and it is essential that we separate statements and opinions from the clinical evidence produced by high-quality research studies. Careful consideration should be given to the totality of evidence in this debate including the highest level of evidence from human clinical studies. It seems premature to provide human mechanistic studies as proof of harm in the absence of clear evidence of adverse effects of fructose on clinically meaningful outcomes. The major question that needs to be answered is: is there something special about fructose metabolism that increases the risk of obesity and chronic disease, or is the harm is related just to the excess calories it provides. In this review, we aim to present a synthesis of the highest quality evidence involving human subjects to answer this question.Figure Prospective cohort studies are characterized by a long-term longitudinal follow-up, good measurement of dietary exposures, superior ascertainment of incidence of disease and mortality outcomes (and not just surrogate markers) and the ability to adjust for multiple confounding factors . These aA WHO-commissioned systematic review and meta-analysis of prospective cohort studies did not find any association between total fructose-containing sugars and body weight . SimilarRegular consumption of SSBs indicates that it can lead to weight gain and substantially increase risk of developing cardiometabolic diseases . A WHO-cMeanwhile, pooled analyses involving many of the same prospective cohort studies that were used in the analysis of SSBs did not find harmful relationships between type 2 diabetes and total dietary sources of sugars (liquid or solid), total sucrose, total fructose  or otherThe contrast of results between sugars provided by SSBs and sugars from other food sources is striking; the former shows a consistent signal of harm, while the latter shows either no harm or a benefit. These results suggest that sugars from SSBs might be a special case and this assertion is supported by several plausible explanations. One, the association might be related to energy as the observed associations between SSBs and cardiometabolic diseases only remain significant at the highest quantiles of exposures and do not remain significant at mean levels of exposures for USA, the exception being gout . The disAnalysis of food consumption as dietary patterns offer a more comprehensive approach to the relationship between diet and disease and as such might shed a light on what foods, which might in themselves be associated with disease, are taken along with SSBs. The Harvard cohorts  have revealed two distinct dietary patterns. One is the Western dietary pattern, which is characterized by high intakes of SSBs, processed meats, red meats, refined grains, French fries, sweets and desserts, and the second is the prudent dietary pattern characterized by high intakes of vegetables, fruit, legumes, fish, poultry and whole grains. The Western dietary pattern is associated with increased cardiometabolic disease outcomes that includes weight gain, increased risk of diabetes, CHD and mortality resulting from CHD in energy-adjusted models –83. In fThere are some important caveats to the clear and consistent relationship between SSBs and cardiometabolic disease. The associations for SSBs are only significant when comparing extreme comparisons, i.e. typically ≥1–2 servings/day versus none or <1 serving/month, or an increase in energy consumption from each additional serving/day. No significant associations have been seen at moderate levels of intake , 62, 91,How does a moderate consumption of SSBs contribute to the burden of disease at a global level? The recent Global Burden of Disease Study used national level data on 67 measured risk factors for disease including SSB consumption worldwide . The autIf we take a look at the potential risk of individual diseases, the effect sizes associated with SSBs tend to be relatively modest. For example, pooled relative risk (RR) for SSBs with cardiometabolic diseases including metabolic syndrome  , diabeteThe relatively modest risk ratios of the association of per serving increase in SSB intake with cardiometabolic diseases begs the question, if other sources of calories in the diet are more important than SSBs? A pooled analyses of the three Harvard cohorts by Mozaffarian et al.  found thOverall, the evidence we presented suggests that SSBs have comparatively small effect sizes seen only at the extremes of intake, which makes them an important source of excess sugary calories but not something that unusually contributes to increased cardiometabolic risk compared to many other aspects of the diet when we consider their mean intake globally.High-quality evidence from randomized and non-RCTs offers the best protection from bias as these control for confounding factors while allowing for the isolation of the effect of interest. The major limitation of nutrition trials of dietary sugars is the lack of clinical outcomes as these require long-term follow-up over years and most nutrition trials last only a few weeks. However, risk factors or surrogate outcomes measured at intermediate times can be explored with good precision, thereby providing insight into processes that might lead to disease.We can use two types of trial designs together to disentangle the direct association of various risk factors with fructose intake from the energy it provides. One, substitution trials, in which comparisons are matched for energy, with fructose, in liquid or mixed format, is substituted for other sources of carbohydrates in the diet. The substitution trials can provide information on the usefulness of low-sugar foods on shelves, which are usually backfilled with other carbohydrates including starch and maltodextrins, so in many cases the total amount of calories do not change . The secIn a Canadian Institute of Health Research (CIHR) funded series of systematic reviews and meta-analyses of controlled trials consisting of more than 50 trials and an excess of 1000 subjects, we examined the effect of fructose on various cardiometabolic risk factors when it was provided in isocaloric substitution for other carbohydrates see Fig. . In the Conversely, the adverse effect of fructose in isocaloric trials is seen only under certain conditions. The dose threshold of harm for the effect of fructose on fasting triglycerides has been reported as >60 g/day in people with type 2 diabetes and >100 g/day in those with mixed phenotypes, and a threshold of >50 g/day for postprandial triglycerides in those with mixed phenotypes , 118. FrWhy would fructose show benefit on HbA1c or glycated haemoglobin in low doses? Fructose might be needed in smaller amounts as it is sweeter than glucose. The relative sweetness in a 10% solution for fructose is 117, glucose is 65, and sucrose is 100 . AlthougSimilar to rodent studies of overfeeding where we see a consistent signal for harm , in humaA criticism that can be levelled on the systematic reviews and meta-analyses of controlled trials of fructose described above is that in diet pure fructose is not consumed in isolation but is commonly consumed together with glucose, either in form of HFCS or honey, or as part of the sucrose molecule. In other words, it can be argued that the above studies do not represent real-world situations for the vast majority of people. For this reason, we investigated the trials of fructose-containing sugars  found normally in the diet and examined their effects on cardiometabolic outcomes. To allow the direct effects of fructose-containing sugars to be disentangled from calories, four types of study designs can be described: (1) substitution trials, in which fructose-containing sugars added to foods and beverages are compared with other macronutrient sources under energy-matched conditions; (2) addition trials, in which fructose-containing sugars supplemented a diet with excess energy compared to the same diet supplemented with the equivalent amounts of non-caloric food and beverages or the same diet alone without the excess energy from fructose-containing sugars; (3) subtraction trials, in which energy from fructose-containing sugars was reduced through displacement with water and/or no-calorie or low-calorie sweeteners or by eliminating it altogether from the background diet; and (4) ad libitum trials, in which energy from fructose-containing sugars was freely replaced with other foods like complex carbohydrates and fat without any strict control of either the study foods or the background diet.Two separate systematic reviews and meta-analyses of substitution trials showed no difference for fructose-containing sugars on bodyweight when they were replaced isocalorically with other macronutrient sources  see Fig. . The firA follow-up systematic review and meta-analysis by the same WHO group showed mixed effects of fructose-containing added sugars on other cardiometabolic risk factors . In thisHow does fructose-containing sugars fare against macronutrients other than carbohydrates, e.g. fat and protein? Most studies comparing fructose-containing sugars with fat and protein used SSBs as the form of dietary sugars. Looking at weight gain, no difference in body weight or total body fat was seen when SSBs were substituted isocalorically for milk in a trial in children for 16 months  and in aCompared to substitution trials, consistent signal of harm was seen in the addition trials. Four systematic reviews and meta-analyses found that supplementing the diet with excess energy from fructose-containing sugars resulted in significant weight gain when compared with the same diets alone without the excess energy see Fig. . The firIn the pooled analyses of subtraction trials in which calories in the diet provided by fructose-containing sugars (as added sugars or SSBs) are removed and replaced with water or non-caloric beverages, results have not shown a consistent associated with weight loss , 55, 140Few randomized trials have assessed the effect of displacing calories from sugars using no- or low-calorie sweeteners or water on cardiometabolic risk factors. The systematic review and meta-analysis by WHO group  of 39 trAd libitum trials reflect real-world patterns to assess the effect of replacing fructose-containing sugars with other nutrients on weight gain and downstream cardiometabolic risk beyond the calories they provide. In these studies, fructose-containing sugars are freely replaced with other sources of energy in the diet without any requirement of a predetermined load nor a strict control of replacement or the background diet. We found very few studies with such design. The largest and the longest duration ad libitum trial was the CArbohydrate Ratio Management in European National Diets (CARMEN) study . It compA lesson we can learn from the fat paradigm is that there can be unintended consequences of focusing singly on one nutrient. When saturated fat was deemed harmful, the industry responded by producing low-fat products, with no resultant appreciable calorie change, as in these products calories from fat were replaced with calories from other sources, e.g. starches and other sugars like maltodextrins . The pubIf a similar approach is taken by the industry who producing ‘low-sugar’ food products, a replay of the above scenario looks likely. Furthermore, the unique functional properties of fructose-containing sugars mean that their replacement is not as easy as it sounds. The functions provided in food products by sugars are related to their sensory , physical , microbial (preservation and fermentation) and chemical (inversion and caramelization) properties . TherefoDespite the continuing concern regarding fructose’s unique metabolic effects, which stems from low-quality ecological studies, animal models and select human studies, the highest level of evidence from systematic review and meta-analysis does not support a direct causal relationship with cardiometabolic disease. Using the totality of the highest quality evidence from controlled feeding trials, we demonstrate that fructose-containing sugars can lead to weight gain, increase in cardiometabolic risk factors and disease only if it provides the excess calories. When the calories are matched, fructose-containing sugars do not appear to cause weight gain compared to other forms of macronutrients including complex carbohydrates, fats and protein, and in low doses fructose might even show benefit. Prospective cohort studies, which provide the strongest observational evidence, have shown an association between fructose-containing sugars and cardiometabolic risk including weight gain, cardiovascular disease outcomes and diabetes only when restricted to SSBs and not for sugars from other sources. In fact, the harmful effect of SSBs is likely driven by a collinearity with an unhealthy lifestyle as SSB drinkers consume more calories, exercise less, smoke more and have a poor dietary pattern.In summary, there is nothing unique about the sugar, fructose. It is harmful when in excess but potentially beneficial when taken in small amounts—providing evidence that it is the excess energy that is causing harm and not some unique metabolic effect. Still, the potential for overconsumption of sugars in form of sugary foods and drinks is substantial, and targeting added sugars as a source of excess calories appears to be a prudent strategy. However, sugar content should not be seen as the sole determinant of a healthy diet. There are many other factors in the diet—some providing excess calories while others provide beneficial nutrients. We should consider the whole diet for health benefits compared to just focusing on one nutrient. In this regard, improvements in dietary patterns appear to have the greatest influence on weight gain and cardiometabolic risk and represent the best opportunity for successful intervention.


Gall-inducing insects are capable of exerting a high level of control over their hosts’ cellular machinery to the extent that the plant’s development, metabolism, chemistry, and physiology are all altered in favour of the insect. Many gallers are devastating pests in global agriculture and the limited understanding of their relationship with their hosts prevents the development of robust management strategies. Omics technologies are proving to be important tools in elucidating the mechanisms involved in the interaction as they facilitate analysis of plant hosts and insect effectors for which little or no prior knowledge exists. In this review, we examine the mechanisms behind insect gall development using evidence from omics-level approaches. The secretion of effector proteins and induced phytohormonal imbalances are highlighted as likely mechanisms involved in gall development. However, understanding how these components function within the system is far from complete and a number of questions need to be answered before this information can be used in the development of strategies to engineer or breed plants with enhanced resistance. The ability to induce galls is a specialised feeding behaviour that requires a close host-pest adaptation . Insect Daktulosphaira vitifolia) and grape (Vitis vinifera), the Hessian fly (Mayetiola destructor) and wheat (Tritcum aestivum), the Asian rice gall midge (Orseolia oryzae) and rice (Oryza sativa), the blue gum chalcid wasp (Leptocybe invasa) and Eucalyptus spp., as well as root-knot nematodes (Meloidogyne spp.) and a wide range of hosts amongst numerous other examples. The development of resistant plant genotypes through breeding or genetic modification is a commonly used approach to control these pests; however, resistance is often rapidly overcome by more virulent insect biotypes ,7560,75]Plant-insect interactions are increasingly being investigated using omics technologies . One of In the last decade omics technologies have provided a new and potent means for improving the knowledge of plant-galling insect interactions. In order to initiate gall induction, it is essential that the insect assume control of its host’s cellular machinery. There is a growing body of evidence supporting the involvement of a diverse array of effector proteins and induced phytohormonal imbalances in galling. However, to interrogate an interaction, a controlled and reliable plant-pest system must be developed a. MicrosA. thaliana and two pathogens to demonstrate that pathogen effectors tend to target hubs in the plant immune response network. A similar approach  could synthesise IAA and cytokinin precursors was a significant breakthrough in this field [While studies have demonstrated differential expression of hormone synthesis and responsive genes, as well as hormone concentrations, the regulatory functions of the hormones in many plant-galling insect interactions remain unknown ,16,31. Mis field . WhetherCastanea species was recently reported to cause extensive mortality in Asian chestnut gall wasp (Dryocosmus kuriphilus) populations [Studies exploring the role of microbial associates in insect galler lifecycles are rare. Symbiotic relationships between gall-inducing insects and microbes have been hypothesised to be involved in gall development, host plant use, and the evolution of the galling trait ,31. The ulations . Metatraulations  and termulations , as wellulations . Spatialulations  may alsoAn important future aim of investigating the plant defence system is to generate a model that accurately simulates the infection or infestation which will allow for the identification of important components . CurrentThe integrative nature of systems biology approaches provides more power in prediction of key targets for functional testing. Knowledge of key components in the plant-insect galler system and their behaviour during the interaction will help identify the most beneficial targets for improved pest management programs. For this purpose, the prediction of important candidate genes that can be explored in more targeted functional genetics experiments will be important. Pending functional characterisation, such targets could be screened for in breeding populations to identify potentially resistant material or adopted as targets of genetic modification using genome editing or RNAi approaches ,85.


Proteomics plays an increasingly important role in our quest to understand cardiovascular biology. Fueled by analytical and computational advances in the past decade, proteomics applications can now go beyond merely inventorying protein species, and address sophisticated questions on cardiac physiology. The advent of massive mass spectrometry datasets has in turn led to increasing intersection between proteomics and big data science. Here we review new frontiers in technological developments and their applications to cardiovascular medicine. The impact of big data science on cardiovascular proteomics investigations and translation to medicine is highlighted. The heart is in many ways an exceptional organ. Proteins at the sarcolemma, sarcomere, mitochondrion, and other cardiac organelles must orchestrate vital functions seamlessly on a beat-by-beat basis, while dynamically adjusting energetic and contractile outputs to environmental cues within seconds. Heart diseases including cardiac hypertrophy and failure are characterized by complex remodeling of various protein signaling networks and subcellular components, which often involve a multitude of collaborating proteins. Therefore, understanding how multiple protein species interact to carry out higher physiological phenotypes and regulation has been an important objective of cardiovascular research. The power of proteomics to simultaneously provide information on the panoply of expressed proteins has made it uniquely suitable for resolving complex signaling conundrums and revealing disease mechanisms in the heart.Advances in genome sequencing are often celebrated to have outpaced even the vaunted Moore’s law of computing power . Lesser Cardiovascular proteomics has grown rapidly in the intervening period, with >400 studies now being published yearly Fig.  3]. To . To 3]. 6 proteolytic peptides per sample. With the addition of post-translational modifications (PTMs)—e.g., the four histone proteins alone have identified PTMs on at least 105 different residues in myriad combinations [An early hurdle that bedeviled cardiovascular proteomics was the limitation in the sensitivity and dynamic range of protein detection, which skewed results towards few high-abundance proteins  and masked low-abundance species. This is due to the complexity of proteomes. The mammalian heart is known to express at least ~8000 genes at significant levels , and at In the past decade, great strides have been made to improve proteome coverage, from how protein samples are extracted to mass spectrometry instrumentation. To perform proteomics analysis, it follows that the proteins must be effectively extracted and released from biological samples. This is typically achieved via mechanical homogenization or chemical surfactants. Protein solubilization techniques in early proteomics protocols were at times ineffectual in extracting hydrophobic or membrane proteins, which often aggregated out of the sample and led to their non-detection. Development in this area in recent years have led to commercially available, mass spectrometry compatible surfactants , size exAdvances in separation sciences have had a particularly tremendous impact on reducing the complexity of peptides prior to mass spectrometry signal acquisition. High-performance shotgun proteomics using mass spectrometry has supplanted two-dimensional 2D) electrophoresis to become the de facto standard for large-scale analysis of cardiac proteins , sensitivity , and mass resolution (increasing power to differentiate similar peptide species). Recent proteome profiling experiments of the mammalian heart using the latest and greatest LC–MS combinations routinely achieve 5000 or more proteins identified in an experiment Fig. b. In a rTaken together, these advances have helped solve a principal challenge to proteomics applications, namely how to successfully detect the maximal number of peptides inside the overwhelmingly complex mixture that is the cardiac proteome. Although each technological development is incremental, over time they accrued into a qualitative transformation on the power and utility of proteomics, when proteins of biomedical interest gradually became measurable and discoverable in large-scale experiments. Catalogs of so-called “complete proteomes”  have now been described for many human tissues and organs, including the heart , 20. TheEarly applications were also plagued by the variability of quantification results, which limited power to discover significant changes between disease model and control samples. A major source of variability in proteomics quantification originated from the variable detectability of peptides with different amino acid compositions. Two equimolar peptide sequences can show rather different intensities in MS signals. Accurate prediction of peptide intensity based on sequence information remains an unsolved issue in computational proteomics due to the large number of combinatorial variables that contribute to signal behaviors. Several methods have been developed to normalize peptide intensity and achieve accurate quantification. Targeted MS methods, such as Multiple Reaction Monitoring (MRM) , allow uWith advances in data acquisition methods, non-targeted label-free techniques can also reliably deduce accurate protein intensity from shotgun experiments directly through bioinformatics analysis. Label-free quantification is analogous to deducing transcript abundance from read counts in next-generation sequencing. Existing approaches largely fall into two categories Fig. . SpectraThe massive amount of MS data generated in proteomics experiments requires computational aid for effective data processing and analysis. A growing number of open-access computational tools concerning all steps of proteomics data analysis are now freely available to users, a subset of which are listed in Table A major computational task in shotgun proteomics is to efficiently interpret the mass and intensity information within mass spectral data to identify proteins. The computational task can be formulated thus: given a particular tandem mass spectrum, identify the peptide sequences most likely to have given rise to the set of observed parent molecular mass and fragment ion patterns in a reasonable time frame. A general solution to this problem is “database search”, which involves generating theoretical spectra based on in silico fragmentation of peptide sequences contained in a protein database, and then systematically comparing the experimental MS spectra against the theoretical spectra to find the best peptide-spectrum matches. The SEQUEST algorithm was the first proposed to solve this peptide spectrum matching problem in 1994  and its Means to distinguish true and false positives are critical to all large-scale approaches. The “two-peptide rule” was once commonly adopted to decrease false positives at the protein level by requiring each protein to be identified by at least two independent peptides. However, this rather conservative rule could inflate false negatives, as some short or protease-incompatible proteins may only produce maximally one identifiable peptide. More recent conventions involve foregoing the two-peptide rule and instead estimating the false discovery rate (FDR) of identification through statistical models, often with the aid of decoy databases. The use of decoy databases/sequences (reversed or scrambled peptide sequences), allows a quick estimation of the number of false positive proteins, by assuming identical distribution in protein identification scores for false positive hits and the decoy hits. A maximum acceptable FDR can then be specified  to determine which protein identifications are accepted in the final result. To explicitly reveal the posterior probability of any particular identification being correct , a mixture model has been used that assumes that the peptide identification result is a mixture of correct and incorrect peptides with two distinct Poisson distributions of identification scores . AuxiliaWith the increase in data size and multiplexity (number of sample compared) in proteomics experiments, statistical approaches to analyze data have also evolved to tackle high-dimensionality data. Whereas early studies utilized mostly confirmatory statistics, modern proteomics datasets typically contain thousands of features  over a handful of observations, hence simply testing whether each protein is significantly altered across experimental conditions can result in under-analysis and failure to distinguish latent structures across multiple dimensions, e.g., whether there exists a subproteome of co-regulated proteins across multiple treatment categories. To gain biological insights, quantitative proteomics datasets are now routinely mined using statistical learning strategies that comprise feature selection , dimensionality reduction , and both supervised and unsupervised learning  to discern significant protein signatures, disease-implicated pathways, or interconnected co-expression networks Fig. .Fig. 4PrImprovements to computational methods that allow more robust results from label-free quantification are an area of active research. For example, recent works  have attempted to resolve the respective quantities of multiple proteins that share common peptide sequences in spectral counting, either using weighted average methods or more statistically motivated models , 37. In With the proliferation of inter-compatible tools, an ongoing trend is to daisy-chain individual tools into user-friendly pipelines that provide complete solutions to a set of related data analysis problems. An ideal proteomics pipeline may combine identification, quantification, and validation tools in a modular organization accessible from a single location. Computation may be performed on the cloud to avoid the need to repeatedly copy, transfer, and store large files. Researchers can carry out computational tasks remotely from the browser on any computer system, obviating the need for redundant infrastructure investments. Currently, the Trans-Proteomics Pipeline  and the Not unlike other omics approaches, the success of proteomics experiments relies heavily on having adequate and up-to-date resources to analyze large-scale data. To wit, for protein database search to succeed, it follows that the protein being identified must first be documented on a sequence database. Fortunately, there have been tremendous advances on the completeness (number of true positive sequences recorded) and precision  of sequence databases such as UniProt and RefSeq. Some databases are manually curated to contain precise information, whilst others strive to be more comprehensive; but many now list precise “complete proteomes” for commonly studied laboratory species. Databases for human and popular laboratory model organisms have seen particular progress in the completeness of annotation in recent years, such that proteomics studies can now be performed similarly well in mice, drosophila, rats, and other organisms to interrogate cardiac physiology. On the horizon, one can foresee an influx of sequence information on protein polymorphism and alternative splicing isoforms. Although current databases primarily originate from genomic translation or cDNA library of specific cell types or genetic backgrounds, “proteogenomics” efforts are underway to translate additional sequences for proteomics studies, which will expand the scope and precision of protein identification. For non-model organisms, alternative search methods have been devised, such as against a custom database generated by manual six-frame translation of genomic sequences.Data interpretability problems arise when the complex results comprising changes of many proteins could not be easily digested and summarized in terms that are relatable and of value to biomedical and clinical researchers. The biological significance of the implicated protein targets may be interpreted and connected to the growing corpus of biomedical knowledge through functional annotations. Commonly used annotation resources include Gene Ontology for biological functions , ReactomTo map molecular data to curated annotations, a class discovery approach is commonly utilized, which looks for annotated properties that are preferentially shared amongst a subset of proteins with interesting quantitative features over the proteome-wide background, e.g., through sequence motif analysis or annotation term enrichment. The principle behind such analyses is to infer biologically relevant processes based on significant overlaps between data features and the data annotation classes. Computational and statistical approaches are used to determine whether particular annotations are over-represented in a particular subset results than would be expected by chance. This allows both bias-free discovery and specific questions to be asked of a dataset, e.g., whether the down-regulated proteins in a heart failure patient are preferentially involved in fatty acid metabolism, etc. Enrichment analyses can be easily carried out using online tools that perform binomial or hypergeometric tests on the over-representation of functional annotations, including NCBI DAVID, WebGestalt, and Pantherdb –51. For We note that many proteomics functional analysis strategies were originally developed for microarray datasets. Although the analytical goals between proteomics and microarray experiments often overlap, i.e., identify functional associations from numerical molecular expression data, several methodological differences merit considerations. The stochastic nature of shotgun proteomics can lead to missing values and high variability in the data for low-abundance proteins. To address this, several proteomics-focused enrichment analysis tools have recently been developed to address specific features of proteomics datasets, e.g., using weighted sampling, which should account for relative abundance and variability of observations and further improve quantification performance. Monte Carlo sampling approaches have also been used to counter the bias of annotations on high abundance proteins when calculating enrichment significance .As in the case for protein identification, the success of functional analysis is contingent upon the completeness and accuracy of annotations in knowledgebases. Commonly used knowledgebases such as Uniprot and Reactome have steadily improved in size and richness of functional information. Nevertheless, it sometimes remains the case that some classes of annotations are more complete, either because they are easily computable from sequence information  or can be derived from popular experimental designs , and as a result are more likely to turn up in functional enrichment analyses. On the other hand, annotations on higher-level pathophysiology and tissue-specific regulations are more challenging, because a majority of such information is hidden in unstructured free text in the literature. With >2 million cardiovascular related articles alone on PubMed , howeverThe aforementioned analytical and computational advances have enabled novel and noteworthy applications in cardiovascular proteomics. An exciting trend is to venture beyond simply inventorying which proteins are present in the heart or the blood, and into quantifying their dynamic and spatiotemporal properties. Protein complexity necessitates that many parameters are needed to sufficiently describe the overall proteome in a particular physiological state. New methodologies continually arise that enable new insights into protein–protein interactions , proteinWith increased experimental power to detect peptides, rare and hard-to-detect peptides are increasingly analyzable, including many modified by PTMs. Because translational modifications are attached to proteins following synthesis, their chemical identity, position, and fractional quantity cannot be easily predicted from transcripts, necessitating proteomics studies. PTMs have been the focus of proteomics studies for over a decade and these efforts have increasingly begun to bear fruit in various biomedical investigations. In a recent notable example, Lee et al.  used a gEvidence suggests that the current investigations into PTMs have barely scratched the surface of their complexity. Over 380,000 PTM events are documented on the PhosphoSitePlus database , includiThe function and functionality of a protein are modulated to a great extent by the spatial milieu in which it is situated, which in turn dictates the substrates and interacting partners with which it comes across. Ongoing studies into the spatial distributions of cardiac proteins are inventorying the protein compositions in different cardiac organelles, with particular successes in cardiac mitochondria and nucleus proteomes, as elucidated via targeted enrichment of specific organelles. More recent studies in other organs are suggesting the possibility that proteins are actively and constantly translocalizing between organelles in response to cues, which can be measured by combining differential centrifugation, isotope labeling, and machine learning techniques. Recent advances in data analysis have allowed such differential centrifugation techniques to be used for pan-organellar mapping. Instead of enriching only for a pure sample of a particular organelle type, a centrifugation gradient here is matched to a supervised classification algorithm to classify proteins based on their sedimentation behaviors. The average intracellular position of many proteins can therefore be discovered by their grouping with known organellar markers. These approaches can be readily adopted to understand dynamic protein translocalization from one organelle to another, using new analytical frameworks that can quantify protein translocation in differential centrifugation experiments , 72. ThrSecondly, the synthesis rates of proteins have also proven important to tracing the progression of cardiac hypertrophy preceding heart failure. Interests in classical physiology to understand skeletal and cardiac muscle mass gain have propelled technological and software developments aimed at understanding protein turnover, which can be applied to other fields. There have been particular developments in isotope labeling and kinetic modeling methods, which have elucidated the half-life of proteins in many various cellular compartments in the heart –77. DeveThere have been marked improvements in experimental protocols in affinity purification, as well as statistical and data science methods to filter out false positives in pulldown experiments. Chiang et al. recently elucidated the interactome of the protein phosphtase 1 catalytic subunit (PP1c), identifying 78 interacting partners in human heart. The proteomics results found increased binding to PDE5A in paroxysmal atrial fibrillation patients to impair proteins involved in electrical and calcium remodeling, a result that has implications in the understanding and treatment of atrial fibrillation . WaldronAt the same time, there is renewed interest to perform crosslinker studies on a large scale, which in addition to identifying protein–protein interaction partners, can provide information on the topology and protein domains involved in the interactions. Again we note that the development of new proteomics methodologies now necessitates hand-in-hand advances of novel data science solutions almost without exception. An example is the application of chemical cross-linkers in proteomics, which allows the linking of proximal proteins to quantify the degrees and likelihood of protein–protein interactions in their native cellular environment. Cross-linking proteomics experiments are however infeasible without specialized search engines that can consider the combinatorics of crosslinked peptide sequences, and identify interacting proteins whilst controlling for the FDR that result from the quadratic increase of search space , 84.Quantitative shotgun proteomics has developed into a remarkably powerful technology that enables sophisticated questions on cellular physiology to be asked. The total volume of proteomics data generated per year now ranges in the petabytes. This is paralleled by an increasing number of available proteomics datasets in the public domain that can be reused and reanalyzed, with as many as 100 new datasets being made available per month on the proteomics data repository PRIDE . Hence jDespite impressive gains, improvement of protein identification will likely continue to be an area of active research. It is estimated that up to 75–85 % of mass spectra generated in a proteomics experiment can remain unidentified by current data analysis workflows , 86, thuSecondly, advances in protein quantification techniques, via both experimental and computational developments, will likely continue unabated. Many quantification techniques do not take into account the peptides that may become post-translationally modified or otherwise lost in a biological state. Currently, decreases in label-free measured quantity may be confounded by differences in protein modifications, digestion, or ionization, or matrix effects from different samples. For instance, the acquired spectral counts may be inflated by the existence of shared peptides among multiple (documented or undocumented) protein forms  as well Lastly, the identification of unknown or unspecified PTMs will likely see continued progress. Because the multiplicity of the possible modification types on a peptide can shift peptide fragment masses combinatorially, they can greatly inflate the number of possible matches. Efforts are underway to develop custom sequence databases and devise new algorithms to extract information from existing cardiovascular proteomics datasets that is currently “hiding in plain sight”. For instance, algorithms can be used to predict peptide fragment intensity to improve peptide identification . To makeTo summarize, we recall an apt analogy provided by Loscalzo to compare the understanding of cardiac proteome with that of building a house and the genome with that of its floor plan . Genomic


The long term survival of fecal indicator organisms (FIOs) and human pathogenic microorganisms in sediments is important from a water quality, human health and ecological perspective. Typically, both bacteria and viruses strongly associate with particulate matter present in freshwater, estuarine and marine environments. This association tends to be stronger in finer textured sediments and is strongly influenced by the type and quantity of clay minerals and organic matter present. Binding to particle surfaces promotes the persistence of bacteria in the environment by offering physical and chemical protection from biotic and abiotic stresses. How bacterial and viral viability and pathogenicity is influenced by surface attachment requires further study. Typically, long-term association with surfaces including sediments induces bacteria to enter a viable-but-non-culturable (VBNC) state. Inherent methodological challenges of quantifying VBNC bacteria may lead to the frequent under-reporting of their abundance in sediments. The implications of this in a quantitative risk assessment context remain unclear. Similarly, sediments can harbor significant amounts of enteric viruses, however, the factors regulating their persistence remains poorly understood. Quantification of viruses in sediment remains problematic due to our poor ability to recover intact viral particles from sediment surfaces , our inability to distinguish between infective and damaged (non-infective) viral particles, aggregation of viral particles, and inhibition during qPCR. This suggests that the true viral titre in sediments may be being vastly underestimated. In turn, this is limiting our ability to understand the fate and transport of viruses in sediments. Model systems  are also lacking for some key viruses, preventing our ability to evaluate the infectivity of viruses recovered from sediments . The release of particle-bound bacteria and viruses into the water column during sediment resuspension also represents a risk to water quality. In conclusion, our poor process level understanding of viral/bacterial-sediment interactions combined with methodological challenges is limiting the accurate source apportionment and quantitative microbial risk assessment for pathogenic organisms associated with sediments in aquatic environments. There are a multitude of bacteria and viruses naturally present within the aquatic environment of which the vast majority are not derived from humans  or most probable number (MPN)/100 ml for water and 101 to 106 CFU or MPN/100 g wet weight for sediment  to 4 cm in depth  present in the overlying water column  have been utilized as general markers of fecal pollution. Advantages of this approach includes, target specificity  and their greater environmental persistence in comparison to FIOs; typically 3-fold longer under controlled conditions  . However, coliphages correlate better with disease incidence and concentrations of pathogens  theory  has been shown to be related to the growth rate or phase in E. coli predominantly attach to small particles (< 2 μm), increasing the ease by which they are transported and dispersed in the environment  than in those with larger particles , Campylobacter spp., Salmonella spp. and the pathogenic protozoan Cryptosporidium parvum are known for both creating and colonizing existing biofilms in drinking water systems , possess greater resistance to environmental stresses such as acidity and anoxia, thereby increasing the probability of survival  and qPCR have all been utilized for measurement of VBNC bacteria in environmental samples by comparing “total” or “live” bacteria with “culturable counts”  such as the application of resuscitation promotion factors  have been shown experimentally to be useful for measuring the total bacterial population including the VBNC fraction in water but have yet to be applied to sediment , enzyme-linked immunosorbent assay (ELISA), flow cytometry and qPCR or RT-qPCR  can be observed under the light microscope  to the titre which is shed from infected individuals (105–108.g−1) and the high adsorption efficiencies measured in vitro  qPCR/RT-qPCR approaches have been developed  and wastewater (point source) inputs . For a review see Pachepsky and Shelton  and large (>10 μm) particles respectively . However, advances in high throughput sequencing (HTS) have been applied to monitor fecal pollution, on a variety of different environmental matrices including wastewater, drinking water, riverine/coastal waters and ground water  has hampered research in these areas. Significant headway on applying correction factors for viral extractions using internal standards has shed light on the problem of poor extraction efficacy and inhibition of molecular methods. However, these workaround methods have yet to be applied to sediment and do not address the fundamental quantification problems. Environmental monitoring should now apply a holistic approach using novel technologies such as “lab on chip” and structural integrity methods which may improve on site diagnostics and should include tests for viral infectivity where this is lacking, all of which are currently not applied to sediments. Further studies are also required to close the loop between conventional plate count and qPCR based methods in sediments particularly regarding the role of VBNC bacteria (if any) on bathing water quality and human/environmental health. An improved process-level understanding is required to consider if FIOs and pathogens from different sources  have different VBNC or resuscitation potentials. Complete life cycle analysis from terrestrial, fluvial and coastal zones is also required to fully understand the role of sediments in viral transport and infectivity persistence in the environment. Studies which model pathogenic viral abundance to observed FIO numbers have been successfully applied to water and applicability in sediments requires increased attention. Finally, increased acquisition of physiochemical data in addition to routine biological samples will improve our understanding of the fate of viruses, VBNCs and FIOs in sediments and enable the development of suitable environmental risk assessment for microbiological risk of sediments to human health. In conclusion, our poor process-level understanding of viral/bacterial-sediment interactions combined with methodological challenges is limiting accurate source apportionment and quantitative microbial risk assessment for pathogenic organisms associated with sediments in aquatic environments.FH, CG, and KF wrote the manuscript and undertook data analysis. AA, VJ, SM, JM, DJ, and BC provided technical support and reviewed the manuscript. FH, SM, KF, JM and DJ prepared manuscript for submission. All authors have approved the final version to be published. All authors had substantial contributions to the conception and design of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors were commissioned and funded by United Kingdom Water Industry Research Limited to carry out a revised version of this research, which was reported as chapter presented within a technical report. The funding agency did not influence the content of this review.


Saccharomyces cerevisiae is an importantmodel organism that has significantly contributed to the identification ofconserved molecular and cellular determinants of ageing. The nutrient-sensingpathways are well-recognized modulators of longevity from yeast to mammals, buttheir downstream effectors and outcomes on different features of ageing processare still poorly understood. A hypothesis that is attracting increased interestis that one of the major functions of these “longevity pathways” is tocontribute to the maintenance of the proteome during ageing. In support of thishypothesis, evidence shows that TOR/Sch9 and Ras/PKA pathways are importantregulators of autophagy that in turn are essential for healthy cellular ageing.It is also well known that mitochondria homeostasis and function regulatelifespan, but how mitochondrial dynamics, mitophagy and biogenesis are regulatedduring ageing remains to be elucidated. This review describes recent findingsthat shed light on how longevity pathways and metabolic status impactmaintenance of the proteome in both yeast ageing paradigms. These findingsdemonstrate that yeast remain a powerful model system for elucidating theserelationships and their influence on ageing regulation.Ageing is a complex and multi-factorial process that results in the progressiveaccumulation of molecular alterations that disrupt different cellular functions.The budding yeast  Saccharomyces cerevisiae offersan attractive eukaryotic model that has dramatically accelerated ageing research123Ageing is a complex and multi-factorial biological process driven by genetic,environmental and stochastic factors that lead to cellular degeneration and theprogressive decline of multiple physiological functions. The decline of thesefunctions constitutes one of the most important risk factors for the development ofnumerous age-related diseases. The possible combinations of events occurring duringageing make it particularly challenging to reveal the interplay and hierarchicalorder of these events as well as to study their consequences at a molecular level.In the past few decades, various model organisms (invertebrate and vertebrate) andsystems have been extensively exploited to investigate the mechanisms of ageing,including its determinants, risk factors and the so called "longevitypathways". The budding yeast S. cerevisiae provides two separate, but overlapping paradigms forageing studies, replicative lifespan (RLS) and chronological lifespan (CLS). RLSmeasures the number of daughters cells produced by a single mother cell beforesenescence and constitutes a model for studying the ageing of mitotically activecells. CLS determines the time that cells survive in a non-dividing state afterdepletion of nutrient sources in stationary phase and allows for the study of ageingin post-mitotic cells.In this review, the role of metabolism on primary damage responses and the relevanceof mitochondria-specific dysfunction and reactive oxygen species as ageingdeterminants will be discussed in the context of novel insights into interventionsthat extend yeast lifespan, such as caloric restriction and hormesis. This reviewwill particularly focus on the interconnection between nutrient-sensing pathways andthe maintenance of proteostasis during ageing and its study in both yeast paradigmsof ageing.TOR1 or SCH9 causes an increase inboth CLS and RLS 56912Many of the interventions that extend lifespan of diverse organisms, including yeast,flies, worms, fish, rodents, and rhesus monkeys, decrease activity ofnutrient-signaling pathways. In yeast, a reduction in the activity of twonutrient-sensing pathways, the target of rapamycin (TOR)/the serine-threonine kinaseSch9 57Extension of CLS by reduced TOR activity depends on the transcription factors Gis1and Msn2/4, which are activated by Rim15 and lead to an increase in many protectivesystems including glycogen accumulation, glycerol accumulation, anti-oxidant enzymesand mechanisms related to the maintenance of proteostasis, such as heat shockproteins (HSPs) and autophagy , which scavenges thesuperoxide anions 19Inactivation of TOR/Sch9 and Ras/PKA nutrient-sensing pathways can be achieved bycaloric restriction (CR), which is an experimental manipulation that extends thelifespan of a variety of eukaryotic organisms from yeast to mammals 2020The results of numerous studies suggest that the determinants of yeast replicativeand chronological lifespans are distinct, but overlap 33233Although the evidence from many studies implies that both yeast ageing paradigmsinvoke conserved determinants of ageing in multicellular eukaryotes 1SIP2 decreases lifespan 43SNF1 results in shortening of CLS 454748The role of nutrient-sensing pathways as determinants of longevity has beenextensively explored, but the relevance to ageing of new nutrient hubs, often calledmetabolic sensors, is now attracting attention and has become the focus of intenseinvestigation. One metabolic sensor is Snf1, which functions as an energy sensorthat is able to reprogram cellular metabolism in order to restore normal energylevels essential to sustain cell metabolism and to the cellular response todifferent stresses 143539SIR2 decreases yeast RLS, whereas itsoverexpression increases RLS 52Sirtuins, a highly conserved group of NAD+ dependent protein deacetylases thatresponds to high NAD+/NADH ratios, are another type of metabolic linker. Sirtuinsare considered to be ‘‘master regulators’’ of eukaryotic ageing due to pioneeringwork showing that deletion of SIR2 either has no effect or induces a moderateincrease of CLS . Thissuggests that the longevity promoting effects of CR are independent of Sir2 althoughit remains unclear whether CR has an impact on Sir2 activity. The fact that deletionof SIR2 in combination with reduced PKA or Sch9 activity (promotedby CR) leads to an increase of the expression of several stress-resistance genes anda decrease on the rate of DNA mutations that accumulate with age in post-mitoticconditions could explain the absence of CLS effects under CR conditions.The role of Sir2 in yeast CLS appears to be different and it has been mainly assignedas having a pro-ageing role in CLS. Depending on the strain background and growthmedia, deletion of ATG8 and ATG32Although Sir2 is not associated with CR-promoting CLS extension, treatments withresveratrol, an ageing modulator that mimics CR, result in CLS extension bymechanisms that depend on Sir2 Ageing and some ageing-related diseases are linked to impaired protein homeostasis orproteostasis 606364Macroautophagy, herein called autophagy, is one of the cellular proteolytic systemsthat guarantees the quality of proteins and organelles via their sequestrationwithin double-membrane vesicles called autophagosomes that are delivered tolysosomes/vacuoles for degradation 687172Mutant cells defective in autophagy-related genes exhibit reduced CLS in SD minimalmedium compared to control strains Autophagy has been shown to be required for the extension of yeast CLS promoted by CR447679The picture of autophagy’s function in CLS and particularly in CR-mediated lifespanextension is even hazier if we consider the intervention of the metabolic linkersSnf1 and Sir2 on autophagy regulation and ageing. For instance, in the absence ofnitrogen, the depletion of glucose is a positive signal for autophagy induction butin this situation, the Snf1 kinase is involved in regulation Curiously, anti-ageing drugs such as resveratrol, spermidine and rapamycin areautophagic regulators/activators 59Thus, a great deal of evidence supports the model that autophagy and ageing arecoordinately regulated by a network of different signaling pathways, with partialoverlapping branches.c, into the cytosol, or generally burden themetabolic machinery of the cell by decreasing the efﬁciency of ATP generation 88Dysfunctional mitochondria can generate ROS, release cell death-inducing factors,such as cytochrome Mitophagy is intimately connected to mitochondrial dynamics and thus to themitochondria fission/fusion machinery, which in turn is inactivated when abioenergetic collapse takes place. Although in mammalian cells mitophagy is impairedwhen mitochondrial fission is blocked, in yeast the role of mitochondrial dynamicsin mitophagy and mitochondrial quality control has been proposed to be independentof mitochondrial fission machinery . These results also reinforce the role of Sir2 in theregulation of mitophagy during CLS and point to an exploitation ofSIR2 mutant cells to unveil more about mitochondria homeostasisduring ageing. Nevertheless, under proteotoxic stress, we have shown that aderegulated increase in mitophagy leads to a shorter CLS, indicating that similar toautophagy the selective degradation of mitochondria has to be maintained around athreshold above which it aggravates ageing and reduces CLS An important pathway in mitochondrial homeostasis is the retrograde signalingresponse. This pathway compensates the accumulation of mitochondrial dysfunctionsthat occur during ageing and crosstalks with other relevant signaling pathwaysincluding pathways involved in metabolic stress response such as TOR pathway/biogenesis during ageing has been largely ignored. Although it isrecognized that the maintenance of functional mitochondria and the degradation ofdysfunctional ones is a fundamentally important component of ageing, the regulationof these events and how they impact lifespan is poorly understood. This is even moreimportant in the context of ageing, during which biogenesis, and particularlymitochondria biogenesis, is quite limited and cells have to simultaneously integratecatabolic and anabolic signals to avoid triggering cellular pathways that willultimately culminate in death. Therefore, one of the main challenges in ageingresearch is to understand how the events that constitute hallmarks of cellularageing are regulated and interconnected. However, our ability to make sense of thecomplexity of the networks and their branches is limited. In the last decades, yeasthas become not only the leading model for eukaryotic cell biology but also thepioneer organism that has facilitated the establishment of an entirely new approachto study biological modules  called systemsbiology. Systems biology will be helpful to understand ageing and lifespandeterminants through for example large-scale analyses of gene expression andtranscriptional networks, genetic interactions, protein-protein interactions,proteomes, phosphoproteomes, acetylomes, metabolomes or fluxomes. Therefore, webelieve that yeast still have important secrets to divulge relevant to thesequestions and that yeast studies are likely to produce many additional novelfindings relevant to ageing and ageing interventions in mammals, includinghumans.


An important aspect of animal perception and cognition is learning to recognize relationships between environmental events that predict others in time, a form of relational knowledge that can be assessed using sequence-learning paradigms. Humans are exquisitely sensitive to sequencing relationships, and their combinatorial capacities, most saliently in the domain of language, are unparalleled. Recent comparative research in human and nonhuman primates has obtained behavioral and neuroimaging evidence for evolutionarily conserved substrates involved in sequence processing. The findings carry implications for the origins of domain-general capacities underlying core language functions in humans. Here, we synthesize this research into a ‘ventrodorsal gradient’ model, where frontal cortex engagement along this axis depends on sequencing complexity, mapping onto the sequencing capacities of different species. Cross-species studies of sequence processing are providing insights into combinatorial learning in nonhuman animals that may represent evolutionary precursors to human language-related operations.Recent comparative neuroimaging studies in humans and monkeys provide neurobiological evidence for evolutionarily conserved sequencing processes, supported by functionally homologous subregions of frontal cortex in humans and monkeys.These findings point to further development of animal model systems in which the neuronal mechanisms that support these operations can be studied in ways not feasible in humans.A heuristic ‘ventrodorsal gradient’ model is proposed of primate frontal cortex engagement that depends on sequencing complexity. An explanatory dissection of these systems will require a multilevel, cross-species approach. Language-specific and domain-general processes can be compared and contrasted in humans Human language is an unrivalled mode of communication. It reflects our vast combinatorial capacity to generate and recognize an infinite number of novel communicative sequences, combining syntactic knowledge (rules of language) with semantic labels (words and their meanings). Viewed as an evolved neurobiological system, language depends on neurocognitive processes and neural substrates that may be specific to the domain of language . The recent identification of evolutionarily conserved neural substrates provides critical evidence that structured sequence-learning tasks can provide important insights into how language evolved and identify which specific conserved neural processes related to language can be unraveled mechanistically in animal models. More generally, this research also has implications for understanding how the brain supports complex behaviors, such as the ability to perceive the order of temporal relationships in the world Most nonhuman animals do not organize their vocalizations into complex structured sequences in the same way as humans, songbirds, and a few other species A relatively simple sequencing operation, for example, might involve recognizing relationships between two adjacent items in a short sequence e.g., A, which Hierarchically organized sequences, containing nested or recursive relationships between items, have been widely argued to reflect more language-like structures Brodmann Areas 44/45 (BA 44/45) In humans, sequence-learning and processing tasks can engage similar regions of frontal cortex to those involved in processing natural language frontal operculum hypothesisdual neurobiological language systems hypothesisFriederici and colleagues hypothesized that the function of the frontal operculum might be evolutionarily conserved, serving a homologous role in processing adjacent sequencing relationships in humans and extant nonhuman primates  require learning specific rule-based ordering relationships , designed to emulate the types of sequential dependencies found in syntactically structured linguistic sequences. The neural substrates underpinning the processing of variable adjacent sequencing dependencies were assessed in a recent comparative human and macaque monkey fMRI study Despite the number and variety of transitions that must be processed to detect the ordering violations  and brain pathways (arcuate fasciculus) Are input sequences from different sensory modalities  processed by domain-general neural substrates or by modular processes? Although here we have focused on sequences generated by stimuli from one sensory modality, assessing how sequencing operations might hold across sensory modalities can help to further support or clarify notions on domain-general processing.What are the neuronal mechanisms that underpin sequence-processing capabilities? In animal models, brain areas identified by fMRI, for example, can be probed  and perturbed  to establish causal relationships and provide insights into neural systems and circuit mechanisms.Unraveling the evolutionary origins of language has challenged scientists and philosophers for centuries. Recent comparative research has made considerable progress, providing new insights and evidence for evolutionarily conserved behaviors and neural substrates. Building on this, our synthesis of recent behavioral and neuroimaging findings in humans and monkeys allows us to propose a model of primate frontal cortex organization that depends on sequencing complexity. The model specifies evolutionarily conserved functions related to sequencing operations in humans and other primates, and it predicts that human frontal cortical regions, such as areas 44 and 45, may have differentiated to support higher-order combinatorial operations that go beyond the sequence-processing capacities exhibited by nonhuman animals. Understanding the extent to which language-related cognitive abilities are conserved will provide a more complete and satisfying account of the evolution of the human language network. Moreover, this approach can assist in the development of better neurobiological models for understanding the neuronal mechanisms of certain aspects of human communication.


Abscisic acid (ABA) is a sesquiterpene signaling molecule produced in all kingdoms of life. To date, the best known functions of ABA are derived from its role as a major phytohormone in plant abiotic stress resistance. Different organisms have developed different biosynthesis and signal transduction pathways related to ABA. Despite this, there are also intriguing common themes where ABA often suppresses host immune responses and is utilized by pathogens as an effector molecule. ABA also seems to play an important role in compatible mutualistic interactions such as mycorrhiza and rhizosphere bacteria with plants, and possibly also the animal gut microbiome. The frequent use of ABA in inter-species communication could be a possible reason for the wide distribution and re-invention of ABA as a signaling molecule in different organisms. In humans and animal models, it has been shown that ABA treatment or nutrient-derived ABA is beneficial in inflammatory diseases like colitis and type 2 diabetes, which confer potential to ABA as an interesting nutraceutical or pharmacognostic drug. The anti-inflammatory activity, cellular metabolic reprogramming, and other beneficial physiological and psychological effects of ABA treatment in humans and animal models has sparked an interest in this molecule and its signaling pathway as a novel pharmacological target. In contrast to plants, however, very little is known about the ABA biosynthesis and signaling in other organisms. Genes, tools and knowledge about ABA from plant sciences and studies of phytopathogenic fungi might benefit biomedical studies on the physiological role of endogenously generated ABA in humans. There are no special chemical properties that make ABA particularly useful as a signaling molecule, compared to all other potential alternative chemical structures. Despite the kingdom-specific signaling and biosynthesis, there are also commonalities between plants and animals where both plants and animals rely on intracellular free ABA for activation of their receptors  is best known as a phytohormone regulating abiotic stress responses in plants, but ABA biosynthesis has been observed in a phylogenetically wide range of organisms Hartung, , rangingC-methyl-D-erythritol 4-phosphate (MEP) pathway  and ABA has already been found in Aspergillus, Fusarium and many other kinds of saprophytic or parasitic fungi  have several homologs in the mammalian genomes and are thus candidate endogenous biosynthesis genes , and this protein plays an unknown but critical biochemical role in B. cinerea ABA biosynthesis . Considering the long evolutionary distances between fungi and metazoa, it is possible that a conserved metabolic pathway will rely on unrelated proteins filling the same functions in animals and fungi through convergent evolution. Two of the critical ABA biosynthesis steps in Botrytis (BcABA1 and BcABA2) are represented by P450 proteins, and only CYP51 and CYP7 proteins are found in both fungi and metazoa  that can be found in many different kinds of organisms which produce it by different means  can produce low levels of ABA and other plant hormones  are equally elusive as they used to be in plants prior to the discovery of the PYR/PYL/RCAR receptor family, with several ABA-binding proteins being proposed as receptor candidates  results in 70% higher activity  to avoid one potential side effect. One alternative ABA inactivation pathway is a UDP-dependent glycosyl transferase , which inactivates free ABA by conjugating it to glucose   protein  transgenic , the Belgian Foundation Against Cancer, Interuniversity Attraction Poles, Concerted Research Actions (GOA) and the Group-ID Multidisciplinary Research Partnership of Ghent University.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chronic hepatitis B virus (HBV) infection continues to be a major health burden worldwide; it can cause various degrees of liver damage and is strongly associated with the development of liver cirrhosis and hepatocellular carcinoma. The molecular mechanisms determining HBV persistence are not fully understood, but these appear to be multifactorial and the unique replication strategy employed by HBV enables its maintenance in infected hepatocytes. Both the stability of the HBV genome, which forms a stable minichromosome, the covalently closed circular DNA (cccDNA) in the hepatocyte nucleus, and the inability of the immune system to resolve chronic HBV infection are believed to be key mechanisms of HBV chronicity. Since a true cure of HBV requires clearance of intranuclear cccDNA from infected hepatocytes, understanding the mechanisms involved in cccDNA biogenesis, regulation and stability is mandatory to achieve HBV eradication. This review will summarize the state of knowledge on these mechanisms including the impact of current treatments on the cccDNA stability and activity. We will focus on events challenging cccDNA persistence in dividing hepatocytes. Liver disease associated to persistent infection with hepatitis B virus (HBV) continues to be a major health problem of global impact. Even if HBV is not directly cytopathic for the infected cell, the infection leads to a wide spectrum of liver disease spanning from acute resolving to chronic infection with different grades of hepatitis, which often progresses to liver cirrhosis and hepatocellular carcinoma . In spit+-taurocholate cotransporting polypeptide (NTCP) .,74.73,74Such findings point out the important role that immune modulating factors play in reducing cccDNA loads and activity. We speculate that both direct killing of infected cells and compensatory proliferation of HBV-infected hepatocytes play a key synergistic role in the process of resolving acute hepatitis. This process might have also been functional in chronically HBV infected patients, which were reported to achieve more beneficial treatment outcomes when the stopping of long-term NA therapy was accompanied with a transitory hepatic flare ,51,80.In sum, even if elimination of the cccDNA from the infected liver remains challenging and more research is needed to develop therapeutic approaches boosting HBV-specific immune responses or agents directly targeting the cccDNA, cell division appears to be a natural Achilles’ heel in HBV persistence. At the same time, key factors produced by immune cells, like IFNs and tumor necrosis factor α, can further promote non-cytolytic inhibition of HBV replication and contribute to cccDNA destabilization . The fac


Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales.Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of  During the last 40 years, there have been significant global increases in the intensity and duration of droughts, and current climate models predict this trend will continue in the future . AlthougDrought stress occurs when soil water content is so low that trees can no longer maintain normal life processes. Physiological responses to drought vary as a function of the relative decrease in water availability (drought intensity) and the length of the event (drought duration) (reviewed by ). In theThe physiological consequences of water stress also vary with stand- and tree-level factors. For instance, within a species, drought-induced mortality of overstory trees can vary substantially among stands of different forest types  as well Abies pinsapo with high levels of competition suffered greater growth declines during dry periods and suggested that the interacting effects of competition and drought contribute to drought-induced mortality. However, suppressed trees are also exposed to substantially different environmental conditions compared to dominant trees, including lower wind velocity, temperature and vapor pressure deficit ) Pinus sylvestris were mostly determined by tree-level factors, but that large-scale climatic differences (measured across 393 plots with an 800 m elevation gradient) were relatively unimportant. Here, we found that site-to-site variability in the total amount of precipitation received was a highly significant factor influencing resistance, but not resilience. This suggests that the variation in response among forest types is most likely due to broad-scale gradients in precipitation and water availability. This finding is consistent with the results of Adams and Kolb [Although the relationship between competition and resistance was significant, the proportion of the variance in RWI at the individual tree-level was lowest in 2001, while variance at the broader spatial scales, particularly the forest type level, was quite high . These results counter those of Martínez-Vilalta et al. , who fouand Kolb , who shothe dividing point separating resistance from resilience. This approach allowed us to characterize recovery following a drought event and reveal trends that might have been lost in an analysis of growth responses averaged over multiple years. Better and more consistent tree-ring-based metrics for measuring drought resistance and resilience would increase our ability to synthesize results to increase predictive power and better inform future forest management decisions.Ultimately, a rigorous understanding of tree responses to drought will require careful consideration of several factors not addressed in this study including the role of genetic variability—both within populations and along environmental gradients –as well