Stoichiogenomics: the evolutionary ecology of macromolecular elemental composition

Genome-material costs and functional trade-offs in the autopolyploid Solidago gigantea (giant goldenrod) series

PREMISE

Increased genome-material costs of N and P atoms inherent to organisms with larger genomes have been proposed to limit growth under nutrient scarcities and to promote growth under nutrient enrichments. Such responsiveness may reflect a nutrient-dependent diploid versus polyploid advantage that could have vast ecological and evolutionary implications, but direct evidence that material costs increase with ploidy level and/or influence cytotype-dependent growth, metabolic, and/or resource-use trade-offs is limited.

METHODS

We grew diploid, autotetraploid, and autohexaploid Solidago gigantea plants with one of four ambient or enriched N:P ratios and measured traits related to material costs, primary and secondary metabolism, and resource-use.

RESULTS

Relative to diploids, polyploids invested more N and P into cells, and tetraploids grew more with N enrichments, suggesting that material costs increase with ploidy level. Polyploids also generally exhibited strategies that could minimize material-cost constraints over both long (reduced monoploid genome size) and short (more extreme transcriptome downsizing, reduced photosynthesis rates and terpene concentrations, enhanced N-use efficiencies) evolutionary time periods. Furthermore, polyploids had lower transpiration rates but higher water-use efficiencies than diploids, both of which were more pronounced under nutrient-limiting conditions.

CONCLUSIONS

N and P material costs increase with ploidy level, but material-cost constraints might be lessened by resource allocation/investment mechanisms that can also alter ecological dynamics and selection. Our results enhance mechanistic understanding of how global increases in nutrients might provide a release from material-cost constraints in polyploids that could impact ploidy (or genome-size)-specific performances, cytogeographic patterning, and multispecies community structuring.

Microbes drive metabolism, community diversity, and interactions in response to microplastic-induced nutrient imbalance

The impact of conventional and biodegradable microplastics on soil nutrients (carbon and nitrogen) has been widely examined, and the alteration of nutrient conditions further influences microbial biosynthesis processes. Nonetheless, the influence of microplastic-induced nutrient imbalances on soil microorganisms (from metabolism to community interactions) is still not well understood. We hypothesized that conventional and biodegradable microplastic could alter soil nutrients and microbial processes. To fill this knowledge gap, we conducted soil microcosms with polyethylene (PE, new and aged) and polylactic acid (PLA, new and aged) microplastics to evaluate their effects on the soil enzymatic stoichiometry, co-occurrence interactions, and success patterns of soil bacterial communities. New and aged PLA induced soil N immobilization, which decreased soil mineral N by 91-141 %. The biodegradation of PLA led to a higher bioavailable C and wider bioavailable C:N ratio, which further filtered out specific microbial species. Both new and aged PLA had a higher abundance of copiotrophic members (Proteobacteria, 35-51 % in PLA, 26-34 % in CK/PE treatments) and rrn copy number. The addition of PLA resulted in a lower alpha diversity and reduced network complexity. Conversely, because of the chemically stable hydrocarbon structure of PE polymers, the new and aged PE microplastics had a minor effect on soil mineral N, bacterial community composition, and network complexity, but led to microbial C limitation. Collectively, all microplastics increased soil C-, N-, and P -acquiring enzyme activities and reduced the number of keystone species and the robustness of the co-occurrence network. The PLA treatment enhanced nitrogen fixation and ureolysis, whereas the PE treatment increased the degradation of recalcitrant carbon. Overall, the alteration of soil nutrient conditions by microplastics affected the microbial metabolism and community interactions, although the effects of PE and PLA microplastics were distinct.

Microbial and Viral Genome and Proteome Nitrogen Demand Varies across Multiple Spatial Scales within a Marine Oxygen Minimum Zone

Nutrient availability can significantly influence microbial genomic and proteomic streamlining, for example, by selecting for lower nitrogen to carbon ratios. Oligotrophic open ocean microbes have streamlined genomic nitrogen requirements relative to those of their counterparts in nutrient-rich coastal waters. However, steep gradients in nutrient availability occur at meter-level, and even micron-level, spatial scales. It is unclear whether such gradients also structure genomic and proteomic stoichiometry. Focusing on the eastern tropical North Pacific oxygen minimum zone (OMZ), we use comparative metagenomics to examine how nitrogen availability shapes microbial and viral genome properties along the vertical gradient across the OMZ and between two size fractions, distinguishing free-living microbes versus particle-associated microbes. We find a substantial increase in the nitrogen content of encoded proteins in particle-associated over free-living bacteria and archaea across nitrogen availability regimes over depth. Within each size fraction, we find that bacterial and viral genomic nitrogen tends to increase with increasing nitrate concentrations with depth. In contrast to cellular genes, the nitrogen content of virus proteins does not differ between size fractions. We identified arginine as a key amino acid in the modulation of the C:N ratios of core genes for bacteria, archaea, and viruses. Functional analysis reveals that particle-associated bacterial metagenomes are enriched for genes that are involved in arginine metabolism and organic nitrogen compound catabolism. Our results are consistent with nitrogen streamlining in both cellular and viral genomes on spatial scales of meters to microns. These effects are similar in magnitude to those previously reported across scales of thousands of kilometers. IMPORTANCE The genomes of marine microbes can be shaped by nutrient cycles, with ocean-scale gradients in nitrogen availability being known to influence microbial amino acid usage. It is unclear, however, how genomic properties are shaped by nutrient changes over much smaller spatial scales, for example, along the vertical transition into oxygen minimum zones (OMZs) or from the exterior to the interior of detrital particles. Here, we measure protein nitrogen usage by marine bacteria, archaea, and viruses by using metagenomes from the nitracline of the eastern tropical North Pacific OMZ, including both particle-associated and nonassociated biomass. Our results show higher genomic and proteomic nitrogen content in particle-associated microbes and at depths with higher nitrogen availability for cellular and viral genomes. This discovery suggests that stoichiometry influences microbial and viral evolution across multiple scales, including the micrometer to millimeter scale associated with particle-associated versus free-living lifestyles.

Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs

BACKGROUND AND AIMS

Plant tissue nitrogen (N) and phosphorus (P) and genome traits, such as genome size and guanine-cytosine (GC) content, scale with growth or metabolic rates and are linked to plant ecological strategy spectra. Tissue NP stoichiometry and genome traits are reported to affect plant growth, metabolic rates or ecological strategies in contrasting ways, although the elemental costs for building and maintaining DNA are typically overlooked.

METHODS

We formulated stoichiometry- and ecology-based predictions on the relationship between genome size and GC content to tissue N, P and N : P and tested them on a set of 130 herbaceous species from a temperate grassland using ordinary, phylogenetic and quantile regression.

KEY RESULTS

Genome size was only negatively linked to plant N and N : P in species with very small genomes. We found no link between genome size and plant P. GC content was negatively linked to plant N and P but we found these significant links consistently in both GC-rich and GC-poor species. Finally, GC content correlated positively with plant N : P but only in species with GC-rich genomes.

CONCLUSIONS

Our results provide stronger support for the ecology-based predictions than the stoichiometry-based predictions, and for the links between GC content and plant N and P stoichiometry than for genome size. We argue that the theories of plant metabolic rates and ecological strategies (resource-acquisitive vs. conservative or ruderal vs. stress-tolerator spectra) better explain interspecific genome-NP stoichiometry relationships at the tissue level (although relatively weakly) than the stoichiometric theory based on the elemental costs for building and maintaining DNA.

Conceptual Exchanges for Understanding Free-Living and Host-Associated Microbiomes

Whether a microbe is free-living or associated with a host from across the tree of life, its existence depends on a limited number of elements and electron donors and acceptors. Yet divergent approaches have been used by investigators from different fields. The "environment first" research tradition emphasizes thermodynamics and biogeochemical principles, including the quantification of redox environments and elemental stoichiometry to identify transformations and thus an underlying microbe. The increasingly common "microbe first" research approach benefits from culturing and/or DNA sequencing methods to first identify a microbe and encoded metabolic functions. Here, the microbe itself serves as an indicator for environmental conditions and transformations. We illustrate the application of both approaches to the study of microbiomes and emphasize how both can reveal the selection of microbial metabolisms across diverse environments, anticipate alterations to microbiomes in host health, and understand the implications of a changing climate for microbial function.

Stoichioproteomics study of differentially expressed proteins and pathways in head and neck cancer

Hypoxia is a prominent feature of head and neck cancer. However, the oxygen element characteristics of proteins and how they adapt to hypoxia microenvironments of head and neck cancer are still unknown. Human genome sequences and proteins expressed data of head and neck cancer were retrieved from pathology atlas of Human Protein Atlas project. Then compared the oxygen and carbon element contents between proteomes of head and neck cancer and normal oral mucosa-squamous epithelial cells, genome locations, pathways, and functional dissection associated with head and neck cancer were also studied. A total of 902 differentially expressed proteins were observed where the average oxygen content is higher than that of the lowly expressed proteins in head and neck cancer proteins. Further, the average oxygen content of the up regulated proteins was 2.54% higher than other. None of their coding genes were distributed on the Y chromosome. The up regulated proteins were enriched in endocytosis, apoptosis and regulation of actin cytoskeleton. The increased oxygen contents of the highly expressed and the up regulated proteins might be caused by frequent activity of cytoskeleton and adapted to the rapid growth and fast division of the head and neck cancer cells. The oxygen usage bias and key proteins may help us to understand the mechanisms behind head and neck cancer in targeted therapy, which lays a foundation for the application of stoichioproteomics in targeted therapy and provides promise for potential treatments for head and neck cancer.

UNSUPERVISED DOMAIN ALIGNMENT BASED OPEN SET STRUCTURAL RECOGNITION OF MACROMOLECULES CAPTURED BY CRYO-ELECTRON TOMOGRAPHY

Cellular cryo-Electron Tomography (cryo-ET) provides three-dimensional views of structural and spatial information of various macromolecules in cells in a near-native state. Subtomogram classification is a key step for recognizing and differentiating these macromolecular structures. In recent years, deep learning methods have been developed for high-throughput subtomogram classification tasks; however, conventional supervised deep learning methods cannot recognize macromolecular structural classes that do not exist in the training data. This imposes a major weakness since most native macromolecular structures in cells are unknown and consequently, cannot be included in the training data. Therefore, open set learning which can recognize unknown macromolecular structures is necessary for boosting the power of automatic subtomogram classification. In this paper, we propose a method called Margin-based Loss for Unsupervised Domain Alignment (MLUDA) for open set recognition problems where only a few categories of interest are shared between cross-domain data. Through extensive experiments, we demonstrate that MLUDA performs well at cross-domain open-set classification on both public datasets and medical imaging datasets. So our method is of practical importance.

Is the genetic code optimized for resource conservation?

The causes and consequences of the nonrandom structure of the standard genetic code (SGC) have been of long-standing interest. A recent study reported that mutations in present-day protein-coding sequences are less likely to increase proteomic nitrogen and carbon uses under the SGC than under random genetic codes, concluding that the SGC has been selectively optimized for resource conservation. If true, this finding might offer important information on the environment in which the SGC and some of the earliest life forms evolved. However, we here show that the hypothesis of optimization of a genetic code for resource conservation is theoretically untenable. We discover that the aforementioned study estimated the expected mutational effect by inappropriately excluding mutations lowering resource consumptions and including mutations involving stop codons. After remedying these problems, we find no evidence that the SGC is optimized for nitrogen or carbon conservation.

The Physics-Biology continuum challenges darwinism: Evolution is directed by the homeostasis-dependent bidirectional relation between genome and phenotype

The physics-biology continuum relies on the fact that life emerged from prebiotic molecules. Here, I argue that life emerged from the coupling between nucleic acid and protein synthesis during which proteins (or proto-phenotypes) maintained the physicochemical parameter equilibria (or proto-homeostasis) in the proximity of their encoding nucleic acids (or proto-genomes). This protected the proto-genome physicochemical integrity (i.e., atomic composition) from environmental physicochemical constraints, and therefore increased the probability of reproducing the proto-genome without variation. From there, genomes evolved depending on the biological activities they generated in response to environmental fluctuations. Thus, a genome maintaining homeostasis (i.e., internal physicochemical parameter equilibria), despite and in response to environmental fluctuations, maintains its physicochemical integrity and has therefore a higher probability to be reproduced without variation. Consequently, descendants have a higher probability to share the same phenotype than their parents. Otherwise, the genome is modified during replication as a consequence of the imbalance of the internal physicochemical parameters it generates, until new mutation-deriving biological activities maintain homeostasis in offspring. In summary, evolution depends on feedforward and feedback loops between genome and phenotype, as the internal physicochemical conditions that a genome generates ─ through its derived phenotype in response to environmental fluctuations ─ in turn either guarantee its stability or direct its variation. Evolution may not be explained by the Darwinism-derived, unidirectional principle (random mutations-phenotypes-natural selection) but rather by the bidirectional relationship between genome and phenotype, in which the phenotype in interaction with the environment directs the evolution of the genome it derives from.

Effects of grassland degradation on ecological stoichiometry of soil ecosystems on the Qinghai-Tibet Plateau

Grasslands across the world are being degraded due to the impacts of overgrazing and climate change. However, the influences of grassland degradation on carbon (C), nitrogen (N), and phosphorus (P) dynamics and stoichiometry in soil ecosystems are not well studied, especially at high elevations where ongoing climate change is most pronounced. Ecological stoichiometry facilitates understanding the biogeochemical cycles of multiple elements by studying their balance in ecological systems. This study sought to assess the responses of these soil elements to grassland degradation in the Qinghai Lake watershed on the Qinghai-Tibet Plateau (QTP), which has an average elevation of >4000 m and is experiencing serious grassland degradation due to its sensitivity and vulnerability to external disturbances. Substituting space for time, we quantified normalized difference vegetation index to gauge grassland degradation. C, N, and P concentrations and their molar ratios in soil and in soil microbial biomass were also measured. The results showed that grassland degradation decreased the concentrations of C and N, as well as the ratios of C:P and N:P in soil. The soil became relatively more P rich and thus N limitation is anticipated to be more apparent with grassland degradation. Moreover, C, N, and P concentrations in soil microbial biomass decreased with increased grassland degradation. C:N:P ratios of soil microbial biomass were highly constrained, suggesting that soil microorganisms exhibited a strong homeostatic behavior, while the variations of microbial biomass C:N:P ratios suggest changes in microbial activities and community structure. Overall, our study revealed that grassland degradation differentially affects soil C, N, and P, leading to decreased C:N and N:P in soil, as well as decreased C, N, and P concentrations in soil microbial biomass. This study provides insights from a stoichiometric perspective into microbial and biogeochemical responses of grassland ecosystems as they undergo degradation on the QTP.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

Stoichioproteomics reveal oxygen usage bias, key proteins and pathways in glioma

Background

The five-year survival rate and therapeutic effect of malignant glioma is low. Identification of key/associated proteins and pathways in glioma is necessary for developing effective diagnosis and targeted therapy of glioma. In addition, Glioma involves hypoxia-specific microenvironment, whether hypoxia restriction influences the stoichioproteomic characteristics of expressed proteins is unknown.

Methods

In this study, we analyzed the most comprehensive immunohistochemical data from 12 human glioma samples and 4 normal cell types of cerebral cortex, identified differentially expressed proteins (DEPs), and researched the oxygen contents of DEPs, highly and lowly expressed proteins. Further we located key genes on human genome to determine their locations and enriched them for key functional pathways.

Results

Our results showed that although no difference was detected on whole proteome, the average oxygen content of highly expressed proteins is 6.65% higher than that of lowly expressed proteins in glioma. A total of 1480 differentially expressed proteins were identified in glioma, including 226 up regulated proteins and 1254 down regulated proteins. The average oxygen content of up regulated proteins is 2.56% higher than that of down regulated proteins in glioma. The localization of differentially expressed genes on human genome showed that most genes were on chromosome 1 and least on Y. The up regulated proteins were significantly enriched in pathways including cell cycle, pathways in cancer, oocyte meiosis, DNA replication etc. Functional dissection of the up regulated proteins with high oxygen contents showed that 51.28% of the proteins were involved in cell cycle and cyclins.

Conclusions

Element signature of oxygen limitation could not be detected in glioma, just as what happened in plants and microbes. Unsaved use of oxygen by the highly expressed proteins and DEPs were adapted to the fast division of glioma cells. This study can help to reveal the molecular mechanism of glioma, and provide a new approach for studies of cancer-related biomacromolecules. In addition, this study lays a foundation for application of stoichioproteomics in precision medicine.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0571-y) contains supplementary material, which is available to authorized users.

Stoichiogenomics reveal oxygen usage bias, key proteins and pathways associated with stomach cancer

Stomach cancer involves hypoxia-specific microenvironments. Stoichiogenomics explores environmental resource limitation on biological macromolecules in terms of element usages. However, the patterns of oxygen usage by proteins and the ways that proteins adapt to a cancer hypoxia microenvironment are still unknown. Here we compared the oxygen and carbon contents ([C]) between proteomes of stomach cancer (hypoxia) and two stomach glandular cells (normal). Key proteins, genome locations, pathways, and functional dissection associated with stomach cancer were also studied. An association of oxygen content ([O]) and protein expression level was revealed in stomach cancer and stomach glandular cells. For differentially expressed proteins (DEPs), oxygen contents in the up regulated proteins were3.2%higherthan that in the down regulated proteins in stomach cancer. A total of 1,062 DEPs were identified; interestingly none of these proteins were coded on Y chromosome. The up regulated proteins were significantly enriched in pathways including regulation of actin cytoskeleton, cardiac muscle contraction, pathway of progesterone-mediated oocyte maturation, etc. Functional dissection of the up regulated proteins with high oxygen contents showed that most of them were cytoskeleton, cytoskeleton associated proteins, cyclins and signaling proteins in cell cycle progression. Element signature of resource limitation could not be detected in stomach cancer for oxygen, just as what happened in plants and microbes. Unsaved use of oxygen by the highly expressed proteins was adapted to the rapid growth and fast division of the stomach cancer cells. In addition, oxygen usage bias, key proteins and pathways identified in this paper laid a foundation for application of stoichiogenomics in precision medicine.

Stoichio-Metagenomics of Ocean Waters: A Molecular Evolution Approach to Trace the Dynamics of Nitrogen Conservation in Natural Communities

Nitrogen is crucially limiting in ocean surface waters, and its availability varies substantially with coastal regions typically richer in nutrients than open oceans. In a biological stoichiometry framework, a parsimonious strategy of nitrogen allocation predicts nitrogen content of proteins to be lower in communities adapted to open ocean than to coastal regions. To test this hypothesis we have directly interrogated marine microbial communities, using a series of metagenomics datasets with a broad geographical distribution from the Global Ocean Sampling Expedition. Analyzing over 20 million proteins, we document a ubiquitous signal of nitrogen conservation in open ocean communities, both in membrane and non-membrane proteins. Efficient nitrogen allocation is expected to specifically target proteins that are expressed at high rate in response to nitrogen starvation. Furthermore, in order to preserve protein functional efficiency, economic nitrogen allocation is predicted to target primarily the least functionally constrained regions of proteins. Contrasting the NtcA-induced pathway, typically up-regulated in response to nitrogen starvation, with the arginine anabolic pathway, which is instead up-regulated in response to nitrogen abundance, we show how both these predictions are fulfilled. Using evolutionary rates as an informative proxy of functional constraints, we show that variation in nitrogen allocation between open ocean and coastal communities is primarily localized in the least functionally constrained regions of the genes triggered by NtcA. As expected, such a pattern is not detectable in the genes involved in the arginine anabolic pathway. These results directly link environmental nitrogen availability to different adaptive strategies of genome evolution, and emphasize the relevance of the material costs of evolutionary change in natural ecosystems.

Subcellular stoichiogenomics reveal cell evolution and electrostatic interaction mechanisms in cytoskeleton

Background

Eukaryotic cells contain a huge variety of internally specialized subcellular compartments. Stoichiogenomics aims to reveal patterns of elements usage in biological macromolecules. However, the stoichiogenomic characteristics and how they adapt to various subcellular microenvironments are still unknown.

Results

Here we first updated the definition of stoichiogenomics. Then we applied it to subcellular research, and detected distinctive nitrogen content of nuclear and hydrogen, sulfur content of extracellular proteomes. Specially, we found that acidic amino acids (AAs) content of cytoskeletal proteins is the highest. The increased charged AAs are mainly caused by the eukaryotic originated cytoskeletal proteins. Functional subdivision of the cytoskeleton showed that activation, binding/association, and complexes are the three largest functional categories. Electrostatic interaction analysis showed an increased electrostatic interaction between both primary sequences and PPI interfaces of 3D structures, in the cytoskeleton.

Conclusions

This study creates a blueprint of subcellular stoichiogenomic characteristics, and explains that charged AAs of the cytoskeleton increased greatly in evolution, which offer material basis for the eukaryotic cytoskeletal proteins to act in two ways of electrostatic interactions, and further perform their activation, binding/association and complex formation.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4845-0) contains supplementary material, which is available to authorized users.

Competitive resource allocation to metabolic pathways contributes to overflow metabolisms and emergent properties in cross-feeding microbial consortia

Resource scarcity is a common stress in nature and has a major impact on microbial physiology. This review highlights microbial acclimations to resource scarcity, focusing on resource investment strategies for chemoheterotrophs from the molecular level to the pathway level. Competitive resource allocation strategies often lead to a phenotype known as overflow metabolism; the resulting overflow byproducts can stabilize cooperative interactions in microbial communities and can lead to cross-feeding consortia. These consortia can exhibit emergent properties such as enhanced resource usage and biomass productivity. The literature distilled here draws parallels between in silico and laboratory studies and ties them together with ecological theories to better understand microbial stress responses and mutualistic consortia functioning.

A Stoichioproteomic Analysis of Samples from the Human Microbiome Project

Ecological stoichiometry (ES) uses organism-specific elemental content to explain differences in species life histories, species interactions, community organization, environmental constraints and even ecosystem function. Although ES has been successfully applied to a range of different organisms, most emphasis on microbial ecological stoichiometry focuses on lake, ocean, and soil communities. With the recent advances in human microbiome research, however, large amounts of data are being generated that describe differences in community composition across body sites and individuals. We suggest that ES may provide a framework for beginning to understand the structure, organization, and function of human microbial communities, including why certain organisms exist at certain locations, and how they interact with both the other microbes in their environment and their human host. As a first step, we undertake a stoichioproteomic analysis of microbial communities from different body sites. Specifically, we compare and contrast the elemental composition of microbial protein samples using annotated sequencing data from 690 gut, vaginal, oral, nares, and skin samples currently available through the Human Microbiome Project. Our results suggest significant differences in both the median and variance of the carbon, oxygen, nitrogen, and sulfur contents of microbial protein samples from different locations. For example, whereas proteins from vaginal sites are high in carbon, proteins from skin and nasal sites are high in nitrogen and oxygen. Meanwhile, proteins from stool (the gut) are particularly high in sulfur content. We interpret these differences in terms of the local environments at different human body sites, including atmospheric exposure and food intake rates.

The Ecology and Evolution of Stoichiometric Phenotypes

Ecological stoichiometry has generated new insights into how the balance of elements affects ecological interactions and ecosystem processes, but little is known about the ecological and evolutionary dynamics of stoichiometric traits. Understanding the origins and drivers of stoichiometric trait variation between and within species will improve our understanding about the ecological responses of communities to environmental change and the ecosystem effects of organisms. In addition, studying the plasticity, heritability, and genetic basis of stoichiometric traits might improve predictions about how organisms adapt to changing environmental conditions, and help to identify interactions and feedbacks between phenotypic evolution and ecosystem processes.

Dietary nitrogen alters codon bias and genome composition in parasitic microorganisms

BACKGROUND

Genomes are composed of long strings of nucleotide monomers (A, C, G and T) that are either scavenged from the organism's environment or built from metabolic precursors. The biosynthesis of each nucleotide differs in atomic requirements with different nucleotides requiring different quantities of nitrogen atoms. However, the impact of the relative availability of dietary nitrogen on genome composition and codon bias is poorly understood.

RESULTS

Here we show that differential nitrogen availability, due to differences in environment and dietary inputs, is a major determinant of genome nucleotide composition and synonymous codon use in both bacterial and eukaryotic microorganisms. Specifically, low nitrogen availability species use nucleotides that require fewer nitrogen atoms to encode the same genes compared to high nitrogen availability species. Furthermore, we provide a novel selection-mutation framework for the evaluation of the impact of metabolism on gene sequence evolution and show that it is possible to predict the metabolic inputs of related organisms from an analysis of the raw nucleotide sequence of their genes.

CONCLUSIONS

Taken together, these results reveal a previously hidden relationship between cellular metabolism and genome evolution and provide new insight into how genome sequence evolution can be influenced by adaptation to different diets and environments.

Evolutionary Dynamics of Chloroplast Genomes in Low Light: A Case Study of the Endolithic Green Alga Ostreobium quekettii

Some photosynthetic organisms live in extremely low light environments. Light limitation is associated with selective forces as well as reduced exposure to mutagens, and over evolutionary timescales it can leave a footprint on species’ genomes. Here, we present the chloroplast genomes of four green algae (Bryopsidales, Ulvophyceae), including the endolithic (limestone-boring) alga Ostreobium quekettii, which is a low light specialist. We use phylogenetic models and comparative genomic tools to investigate whether the chloroplast genome of Ostreobium corresponds to our expectations of how low light would affect genome evolution. Ostreobium has the smallest and most gene-dense chloroplast genome among Ulvophyceae reported to date, matching our expectation that light limitation would impose resource constraints reflected in the chloroplast genome architecture. Rates of molecular evolution are significantly slower along the phylogenetic branch leading to Ostreobium, in agreement with the expected effects of low light and energy levels on molecular evolution. We expected the ability of Ostreobium to perform photosynthesis in very low light to be associated with positive selection in genes related to the photosynthetic machinery, but instead, we observed that these genes may be under stronger purifying selection. Besides shedding light on the genome dynamics associated with a low light lifestyle, this study helps to resolve the role of environmental factors in shaping the diversity of genome architectures observed in nature.

No Evidence That Nitrogen Limitation Influences the Elemental Composition of Isopod Transcriptomes and Proteomes

The field of stoichiogenomics aims at understanding the influence of nutrient limitations on the elemental composition of the genome, transcriptome, and proteome. The 20 amino acids and the 4 nt differ in the number of nutrients they contain, such as nitrogen (N). Thus, N limitation shall theoretically select for changes in the composition of proteins or RNAs through preferential use of N-poor amino acids or nucleotides, which will decrease the N-budget of an organism. While these N-saving mechanisms have been evidenced in microorganisms, they remain controversial in multicellular eukaryotes. In this study, we used 13 surface and subterranean isopod species pairs that face strongly contrasted N limitations, either in terms of quantity or quality. We combined in situ nutrient quantification and transcriptome sequencing to test if N limitation selected for N-savings through changes in the expression and composition of the transcriptome and proteome. No evidence of N-savings was found in the total N-budget of transcriptomes or proteomes or in the average protein N-cost. Nevertheless, subterranean species evolving in N-depleted habitats displayed lower N-usage at their third codon positions. To test if this convergent compositional change was driven by natural selection, we developed a method to detect the strand-asymmetric signature that stoichiogenomic selection should leave in the substitution pattern. No such signature was evidenced, indicating that the observed stoichiogenomic-like patterns were attributable to nonadaptive processes. The absence of stoichiogenomic signal despite strong N limitation within a powerful phylogenetic framework casts doubt on the existence of stoichiogenomic mechanisms in metazoans.

Heterotrophic bacteria from an extremely phosphate-poor lake have conditionally reduced phosphorus demand and utilize diverse sources of phosphorus

Heterotrophic Proteobacteria and Actinobacteria were isolated from Lake Matano, Indonesia, a stratified, ferruginous (iron-rich), ultra-oligotrophic lake with phosphate concentrations below 50 nM. Here, we describe the growth of eight strains of heterotrophic bacteria on a variety of soluble and insoluble sources of phosphorus. When transferred to medium without added phosphorus (P), the isolates grow slowly, their RNA content falls to as low as 1% of cellular dry weight, and 86-100% of the membrane lipids are replaced with amino- or glycolipids. Similar changes in lipid composition have been observed in marine photoautotrophs and soil heterotrophs, and similar flexibility in phosphorus sources has been demonstrated in marine and soil-dwelling heterotrophs. Our results demonstrate that heterotrophs isolated from this unusual environment alter their macromolecular composition, which allows the organisms to grow efficiently even in their extremely phosphorus-limited environment.

Ordinary stoichiometry of extraordinary microorganisms

All life on Earth seems to be made of the same chemical elements in relatively conserved proportions (stoichiometry). Whether this stoichiometry is conserved in settings that differ radically in physicochemical conditions (extreme environments) from those commonly encountered elsewhere on the planet provides insight into possible stoichiometries for putative life beyond Earth. Here, we report measurements of elemental stoichiometry for extremophile microbes from hot springs of Yellowstone National Park (YNP). Phototrophic and chemotrophic microbes were collected in locations spanning large ranges of temperature (24 °C to boiling), pH (1.6-9.6), redox (0.1-7.2 mg L(-1) dissolved oxygen), and nutrient concentrations (0.01-0.25 mg L(-1) NO2-, 0.7-12.9 mg L(-1) NO3-, 0.01-42 mg L(-1) NH4 (+), 0.003-1.1 mg L(-1) P mostly as phosphate). Despite these extreme conditions, the microbial cells sampled had a major and trace element stoichiometry within the ranges commonly encountered for microbes living in the more moderate environments of lakes and surface oceans. The cells did have somewhat high C:P and N:P ratios that are consistent with phosphorus (P) limitation. Furthermore, chemotrophs and phototrophs had similar compositions with the exception of Mo content, which was enriched in cells derived from chemotrophic sites. Thus, despite the extraordinary physicochemical and biological diversity of YNP environments, life in these settings, in a stoichiometric sense, remains much the same as we know it elsewhere.

Composition of distinct sub-proteomes in Myxococcus xanthus: metabolic cost and amino acid availability

Subsets of proteins involved in distinct functional processes are subject to different selective pressures. We investigated whether there is an amino acid composition bias (AACB) inherent in discrete subsets of proteins, and whether we could identify changing patterns of AACB during the life cycle of the social bacterium Myxococcus xanthus. We quantitatively characterised the cellular, soluble secreted, and outer membrane vesicle (OMV) sub-proteomes of M. xanthus, identifying 315 proteins. The AACB of the cellular proteome differed only slightly from that deduced from the genome, suggesting that genome-inferred proteomes can accurately reflect the AACB of their host. Inferred AA deficiencies arising from prey consumption were exacerbated by the requirements of the 68%GC genome, whose character thus seems to be selected for directly rather than via the proteome. In our analysis, distinct subsets of the proteome (whether segregated spatially or temporally) exhibited distinct AACB, presumably tailored according to the needs of the organism's lifestyle and nutrient availability. Secreted AAs tend to be of lower cost than those retained in the cell, except for the early developmental A-signal, which is a particularly costly sub-proteome. We propose a model of AA reallocation during the M. xanthus life cycle, involving ribophagy during early starvation and sequestration of limiting AAs within cells during development.

Nitrogen limitation as a driver of genome size evolution in a group of karst plants

Genome size is of fundamental biological importance with significance in predicting structural and functional attributes of organisms. Although abundant evidence has shown that the genome size can be largely explained by differential proliferation and removal of non-coding DNA of the genome, the evolutionary and ecological basis of genome size variation remains poorly understood. Nitrogen (N) and phosphorus (P) are essential elements of DNA and protein building blocks, yet often subject to environmental limitation in natural ecosystems. Using phylogenetic comparative methods, we test this hypothesis by determining whether leaf N and P availability affects genome sizes in 99 species of Primulina (Gesneriaceae), a group of soil specialists adapted to limestone karst environment in south China. We find that genome sizes in Primulina are strongly positively correlated with plant N content, but the correlation with plant P content is not significant when phylogeny history was taken into account. This study shows for the first time that N limitation might have been a plausible driver of genome size variation in a group of plants. We propose that competition for nitrogen nutrient between DNA synthesis and cellular functions is a possible mechanism for genome size evolution in Primulina under N-limitation.

Impact of genomic diversity in river ecosystems

We propose that genomic diversity in aquatic macrophytes of rivers, driven by the underlying genomic processes of interspecific hybridization and polyploidy (whole-genome duplication), play a significant role in ecosystem functioning. These genomic processes generate individuals which might differ in their demands for nitrogen (N) and phosphorus (P). This is significant because (i) N and/or P are frequently limiting nutrients in freshwater ecosystems, and (ii) nucleic acids are demanding in N and P. We suggest that N and P availability will provide a selection pressure for genetic variants in macrophytes which will, in turn, influence the nutritional quality of plant biomass, and hence their consumption by herbivores and detritivores as well as the energy flux of their biomass through the food web.

Physiological and proteomic analysis of Escherichia coli iron-limited chemostat growth

Iron bioavailability is a major limiter of bacterial growth in mammalian host tissue and thus represents an important area of study. Escherichia coli K-12 metabolism was studied at four levels of iron limitation in chemostats using physiological and proteomic analyses. The data documented an E. coli acclimation gradient where progressively more severe iron scarcity resulted in a larger percentage of substrate carbon being directed into an overflow metabolism accompanied by a decrease in biomass yield on glucose. Acetate was the primary secreted organic by-product for moderate levels of iron limitation, but as stress increased, the metabolism shifted to secrete primarily lactate (∼70% of catabolized glucose carbon). Proteomic analysis reinforced the physiological data and quantified relative increases in glycolysis enzyme abundance and decreases in tricarboxylic acid (TCA) cycle enzyme abundance with increasing iron limitation stress. The combined data indicated that E. coli responds to limiting iron by investing the scarce resource in essential enzymes, at the cost of catabolic efficiency (i.e., downregulating high-ATP-yielding pathways containing enzymes with large iron requirements, like the TCA cycle). Acclimation to iron-limited growth was contrasted experimentally with acclimation to glucose-limited growth to identify both general and nutrient-specific acclimation strategies. While the iron-limited cultures maximized biomass yields on iron and increased expression of iron acquisition strategies, the glucose-limited cultures maximized biomass yields on glucose and increased expression of carbon acquisition strategies. This study quantified ecologically competitive acclimations to nutrient limitations, yielding knowledge essential for understanding medically relevant bacterial responses to host and to developing intervention strategies.

Toward quantitative understanding on microbial community structure and functioning: a modeling-centered approach using degradation of marine oil spills as example

Molecular ecology approaches are rapidly advancing our insights into the microorganisms involved in the degradation of marine oil spills and their metabolic potentials. Yet, many questions remain open: how do oil-degrading microbial communities assemble in terms of functional diversity, species abundances and organization and what are the drivers? How do the functional properties of microorganisms scale to processes at the ecosystem level? How does mass flow among species, and which factors and species control and regulate fluxes, stability and other ecosystem functions? Can generic rules on oil-degradation be derived, and what drivers underlie these rules? How can we engineer oil-degrading microbial communities such that toxic polycyclic aromatic hydrocarbons are degraded faster? These types of questions apply to the field of microbial ecology in general. We outline how recent advances in single-species systems biology might be extended to help answer these questions. We argue that bottom-up mechanistic modeling allows deciphering the respective roles and interactions among microorganisms. In particular constraint-based, metagenome-derived community-scale flux balance analysis appears suited for this goal as it allows calculating degradation-related fluxes based on physiological constraints and growth strategies, without needing detailed kinetic information. We subsequently discuss what is required to make these approaches successful, and identify a need to better understand microbial physiology in order to advance microbial ecology. We advocate the development of databases containing microbial physiological data. Answering the posed questions is far from trivial. Oil-degrading communities are, however, an attractive setting to start testing systems biology-derived models and hypotheses as they are relatively simple in diversity and key activities, with several key players being isolated and a high availability of experimental data and approaches.

Homeostasis: an underestimated focal point of ecology and evolution

BACKGROUND

The concept of homeostasis is often ill-defined, in the scientific literature. The word "homeostasis", literally, indicates the absence of changes and an absolute maintenance of the status quo. The multiplicity of possible examples of homeostasis suggests that it is essentially impossible that all aspects of the composition of the organism and the rate of processes carried out by the organism are simultaneously held constant, when the environment changes are in the non-lethal range.

SCOPE

In attempting to clarify the usage of the term homeostasis, I emphasize the probable contributions to evolutionary fitness of homeostasis main attributes: rate processes and compositions. I also attempted to identify the aspects of homeostasis that are most likely to be subject to natural selection.

CONCLUSIONS

The tendency to retain the status quo derives from the interplay of functions (among which growth), metabolic pools and elemental stoichiometry. The set points around which oscillations occur in biological system and their control mechanisms are determined by evolutionary processes; consequently, also the tendency of a cell to be homeostatic with respect to a given set point is selectable. A homeostatic response to external perturbations may be selectively favored when the potential reproductive advantage offered by a reorganization of cell resources cannot be exploited. This is most likely to occur in the case of environmental perturbations of moderate intensity and short duration relative to the growth rate. Under these circumstances, homeostasis may be an energetically and competitively preferable option, because it requires no alteration of the expressed proteome and eliminates the requirement for reverse acclimation, upon cessation of the perturbation. This review also intends to be a stimulus to "ad hoc" experiments to assess the ecological and evolutionary relevance of homeostasis.

GRASP [Genomic Resource Access for Stoichioproteomics]: comparative explorations of the atomic content of 12 Drosophila proteomes

BACKGROUND

"Stoichioproteomics" relates the elemental composition of proteins and proteomes to variation in the physiological and ecological environment. To help harness and explore the wealth of hypotheses made possible under this framework, we introduce GRASP (http://www.graspdb.net), a public bioinformatic knowledgebase containing information on the frequencies of 20 amino acids and atomic composition of their side chains. GRASP integrates comparative protein composition data with annotation data from multiple public databases. Currently, GRASP includes information on proteins of 12 sequenced Drosophila (fruit fly) proteomes, which will be expanded to include increasingly diverse organisms over time. In this paper we illustrate the potential of GRASP for testing stoichioproteomic hypotheses by conducting an exploratory investigation into the composition of 12 Drosophila proteomes, testing the prediction that protein atomic content is associated with species ecology and with protein expression levels.

RESULTS

Elements varied predictably along multivariate axes. Species were broadly similar, with the D. willistoni proteome a clear outlier. As expected, individual protein atomic content within proteomes was influenced by protein function and amino acid biochemistry. Evolution in elemental composition across the phylogeny followed less predictable patterns, but was associated with broad ecological variation in diet. Using expression data available for D. melanogaster, we found evidence consistent with selection for efficient usage of elements within the proteome: as expected, nitrogen content was reduced in highly expressed proteins in most tissues, most strongly in the gut, where nutrients are assimilated, and least strongly in the germline.

CONCLUSIONS

The patterns identified here using GRASP provide a foundation on which to base future research into the evolution of atomic composition in Drosophila and other taxa.

A metabolic prototype for eliminating tryptophan from the genetic code

We set out to reduce the chemical constitution of a living organism to 19 amino acids. A strain was constructed for reassigning the tryptophan codon UGG to histidine and eliminating tryptophan from Escherichia coli. Histidine codons in the gene for an essential enzyme were replaced with tryptophan codons and the restoration of catalytic activity by missense suppressor His-tRNA bearing a CCA anticodon was selected. We used automated cultivation to assess the stability of this genetic construct during evolution. Histidine to tryptophan mutation at codon 30 in the transketolase gene from yeast and its cognate suppressor tRNA were stably propagated in a tktAB deletant of E. coli over 2500 generations. The ratio of histidine misincorporation at tryptophan sites in the proteome increased from 0.0007 to 0.03 over 300 days of continuous culture. This result demonstrated that the genetic code can be forced to evolve by permanent metabolic selection.

Can resource costs of polyploidy provide an advantage to sex?

The predominance of sexual reproduction despite its costs indicates that sex provides substantial benefits, which are usually thought to derive from the direct genetic consequences of recombination and syngamy. While genetic benefits of sex are certainly important, sexual and asexual individuals, lineages, or populations may also differ in physiological and life history traits that could influence outcomes of competition between sexuals and asexuals across environmental gradients. Here, we address possible phenotypic costs of a very common correlate of asexuality, polyploidy. We suggest that polyploidy could confer resource costs related to the dietary phosphorus demands of nucleic acid production; such costs could facilitate the persistence of sex in situations where asexual taxa are of higher ploidy level and phosphorus availability limits important traits like growth and reproduction. We outline predictions regarding the distribution of diploid sexual and polyploid asexual taxa across biogeochemical gradients and provide suggestions for study systems and empirical approaches for testing elements of our hypothesis.

Mutational bias and gene conversion affect the intraspecific nitrogen stoichiometry of the Arabidopsis thaliana transcriptome

The transcriptome and proteome of Arabidopsis thaliana are reduced in nitrogen content when compared with other taxa, which may result from ecological nitrogen limitation. We hypothesized that if the A. thaliana transcriptome is selected for a low nitrogen content, nitrogen-reducing derived alleles of single nucleotide polymorphisms (SNPs) should segregate at higher frequencies than nitrogen-increasing alleles. This pattern should be stronger in populations with a larger effective population size (N(e)) if natural selection is more efficient in large than in small populations. We analyzed variation in the nitrogen content in the transcriptome of 80 natural accessions of A. thaliana. In contrast to our expectations, derived alleles increase the nitrogen content in all accessions, and there is a positive correlation between nitrogen difference and derived allele frequency, which is strongest with nonsynonymous SNPs (nsSNPs). Also, there is a positive correlation between nitrogen difference and N(e) that was mainly caused by nsSNPs. These observations led us to reject the hypothesis that the transcriptome of A. thaliana is currently under selection to reduce nitrogen content. Instead, we show that a change in nitrogen content is a side effect of interacting evolutionary factors that influence base composition and include mutational bias, purifying selection of functionally deleterious alleles, and GC-biased gene conversion. We provide strong evidence that GC-biased gene conversion may play an important role for base composition in the highly selfing plant A. thaliana.

Plant stoichiometry at different scales: element concentration patterns reflect environment more than genotype

All plant species require at least 16 elements for their growth and survival but the relative requirements and the variability at different organizational scales is not well understood. We use a fertiliser experiment with six willow (Salix spp.) genotypes to evaluate a methodology based on Euclidian distances for stoichiometric analysis of the variability in leaf nutrient relations of twelve of those (C, N, P, K, Ca, Mg, Mn, S, Fe, Zn, B, Cu) plus Na and Al. Differences in availability of the elements in the environment was the major driver of variation. Variability between leaves within a plant or between individuals of the same genotype growing in close proximity was as large as variability between genotypes. Elements could be grouped by influence on growth: N, P, S and Mn concentrations follow each other and increase with growth rate; K, Ca and Mg uptake follow the increase in biomass; but uptake of Fe, B, Zn and Al seems to be limited. The position of Cu lies between the first two groups. Only for Na is there a difference in element concentrations between genotypes. The three groups of elements can be associated with different biochemical functions.

Systems analysis of microbial adaptations to simultaneous stresses

Microbes live in multi-factorial environments and have evolved under a variety of concurrent stresses including resource scarcity. Their metabolic organization is a reflection of their evolutionary histories and, in spite of decades of research, there is still a need for improved theoretical tools to explain fundamental aspects of microbial physiology. Using ecological and economic concepts, this chapter explores a resource-ratio based theory to elucidate microbial strategies for extracting and channeling mass and energy. The theory assumes cellular fitness is maximized by allocating scarce resources in appropriate proportions to multiple stress responses. Presented case studies deconstruct metabolic networks into a complete set of minimal biochemical pathways known as elementary flux modes. An economic analysis of the elementary flux modes tabulates enzyme atomic synthesis requirements from amino acid sequences and pathway operating costs from catabolic efficiencies, permitting characterization of inherent tradeoffs between resource investment and phenotype. A set of elementary flux modes with competitive tradeoffs properties can be mathematically projected onto experimental fluxomics datasets to decompose measured phenotypes into metabolic adaptations, interpreted as cellular responses proportional to the experienced culturing stresses. The resource-ratio based method describes the experimental phenotypes with greater accuracy than other contemporary approaches and further analysis suggests the results are both statistically and biologically significant. The insight into metabolic network design principles including tradeoffs associated with concurrent stress adaptation provides a foundation for interpreting physiology as well as for rational control and engineering of medically, environmentally, and industrially relevant microbes.

Elemental economy: microbial strategies for optimizing growth in the face of nutrient limitation

Microorganisms play a dominant role in the biogeochemical cycling of nutrients. They are rightly praised for their facility for fixing both carbon and nitrogen into organic matter, and microbial driven processes have tangibly altered the chemical composition of the biosphere and its surrounding atmosphere. Despite their prodigious capacity for molecular transformations, microorganisms are powerless in the face of the immutability of the elements. Limitations for specific elements, either fleeting or persisting over eons, have left an indelible trace on microbial genomes, physiology, and their very atomic composition. We here review the impact of elemental limitation on microbes, with a focus on selected genetic model systems and representative microbes from the ocean ecosystem. Evolutionary adaptations that enhance growth in the face of persistent or recurrent elemental limitations are evident from genome and proteome analyses. These range from the extreme (such as dispensing with a requirement for a hard to obtain element) to the extremely subtle (changes in protein amino acid sequences that slightly, but significantly, reduce cellular carbon, nitrogen, or sulfur demand). One near-universal adaptation is the development of sophisticated acclimation programs by which cells adjust their chemical composition in response to a changing environment. When specific elements become limiting, acclimation typically begins with an increased commitment to acquisition and a concomitant mobilization of stored resources. If elemental limitation persists, the cell implements austerity measures including elemental sparing and elemental recycling. Insights into these fundamental cellular properties have emerged from studies at many different levels, including ecology, biological oceanography, biogeochemistry, molecular genetics, genomics, and microbial physiology. Here, we present a synthesis of these diverse studies and attempt to discern some overarching themes.

Dwarf alleles differentially affect barley root traits influencing nitrogen acquisition under low nutrient supply

Sustainable food production depends critically on the development of crop genotypes that exhibit high yield under reduced nutrient inputs. Rooting traits have been widely advocated as being able to influence optimal plant performance, while breeding-based improvements in yield of spring barley suggest that this species is a good model crop. To date, however, molecular genetics knowledge has not delivered realistic plant ideotypes, while agronomic trials have been unable to identify superior traits. This study explores an intermediate experimental system in which root traits and their effect on plant performance can be quantified. As a test case, four modern semi-dwarf barley varieties, which possess either the ari-e.GP or the sdw1 dwarf allele, were compared with the long-stemmed old variety Kenia under two levels of nutrient supply. The two semi-dwarf types differed from Kenia, exhibiting smaller stem mass and total plant nitrogen (N), and improved partitioning of mass and N to grain. Amongst the semi-dwarfs, the two ari-e.GP genotypes performed better than the two sdw1 genotypes under standard and reduced nutrient supply, particularly in root mass, root investment efficiency, N acquisition, and remobilization of N and mass to grain. However, lack of between-genotype variation in yield and N use efficiency indicated limited potential for exploiting genetic variation in existing varieties to improve barley performance under reduced nutrient inputs. Experimental approaches to test the expression of desirable root and shoot traits are scrutinized, and the potential evaluated for developing a spring barley ideotype for low nutrient conditions.

Our microbial selves: what ecology can teach us

Advances in DNA sequencing have allowed us to characterize microbial communities--including those associated with the human body--at a broader range of spatial and temporal scales than ever before. We can now answer fundamental questions that were previously inaccessible and use well-tested ecological theories to gain insight into changes in the microbiome that are associated with normal development and human disease. Perhaps unsurprisingly, the ecosystems associated with our body follow trends identified in communities at other sites and scales, and thus studies of the microbiome benefit from ecological insight. Here, we assess human microbiome research in the context of ecological principles and models, focusing on diversity, biological drivers of community structure, spatial patterning and temporal dynamics, and suggest key directions for future research that will bring us closer to the goal of building predictive models for personalized medicine.