The composition of cellular metabolism is different across species. Empirical data reveal that bacterial species contain similar numbers of metabolic reactions but that the cross-species popularity ...of reactions is so heterogenous that some reactions are found in all the species while others are in just few species, characterized by a power-law distribution with the exponent one. Introducing an evolutionary model concretizing the stochastic recruitment of chemical reactions into the metabolism of different species at different times and their inheritance to descendants, we demonstrate that the exponential growth of the number of species containing a reaction and the saturated recruitment rate of brand-new reactions lead to the empirically identified power-law popularity distribution. Furthermore, the structural characteristics of metabolic networks and the species' phylogeny in our simulations agree well with empirical observations.
Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric ...workflow based on data‐independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non‐metabolic stresses, and non‐planktonic states. The resulting high‐quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low‐abundant proteins under various metabolic limitations, the non‐specificity of catabolic enzymes upregulated under carbon limitation, the lack of large‐scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain‐dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi‐omics studies of gene regulation and metabolic control in E. coli.
Synopsis
Accurate proteomic measurements of absolute protein mass fractions in Escherichia coli allowed the characterization of proteome responses under > 60 diverse growth conditions from a coarse (groups of related proteins) to a fine (individual) protein level.
The study presents a mass spectrometric workflow based on data‐independent acquisition proteomics and a novel protein inference algorithm (xTop) optimized for absolute protein quantification.
The mass spectrometric data was benchmarked and calibrated with absolute protein mass fractions obtained by ribosome profiling.
A plethora of novel biological findings are presented, including lack of large‐scale proteome reallocation under stress compared to nutrient limitations, regulation of outer membrane proteins, and effects important for motility and biofilm formation.
Accurate proteomic measurements of absolute protein mass fractions in Escherichia coli allowed the characterization of proteome responses under > 60 diverse growth conditions from a coarse (groups of related proteins) to a fine (individual) protein level.
(k,q)-core decomposition of hypergraphs Lee, Jongshin; Goh, Kwang-Il; Lee, Deok-Sun ...
Chaos, solitons and fractals,
August 2023, 2023-08-00, Volume:
173
Journal Article
Peer reviewed
Open access
In complex networks, many elements interact with each other in different ways. A hypergraph is a network in which group interactions occur among more than two elements. In this study, first, we ...propose a method to identify influential subgroups in hypergraphs, named (k,q)-core decomposition. The (k,q)-core is defined as the maximal subgraph in which each vertex has at least k hypergraph degrees and each hyperedge contains at least q vertices. The method contains a repeated pruning process until reaching the (k,q)-core, which shares similarities with a widely used k-core decomposition technique in a graph. Second, we analyze the pruning dynamics and the percolation transition with theoretical and numerical methods in random hypergraphs. We set up evolution equations for the pruning process, and self-consistency equations for the percolation properties. Based on our theory, we find that the pruning process generates a hybrid percolation transition for either k≥3orq≥3. The critical exponents obtained theoretically are confirmed with finite-size scaling analysis. Next, when k=q=2, we obtain a unconventional degree-dependent critical relaxation dynamics analytically and numerically. Finally, we apply the (k,q)-core decomposition to a real coauthorship dataset and recognize the leading groups at an early stage.
•A pruning process to obtain the core structure of hypergraphs is proposed.•Theoretical methods to analyze (k,q)-core decomposition are proposed.•The percolation transition of the giant core is studied analytically and numerically.•Degree-dependent power-law behaviors of relaxation dynamics are obtained.•Our method suggests an effective way to select influential subgroup in hypergraphs.
The impact of disease‐causing defects is often not limited to the products of a mutated gene but, thanks to interactions between the molecular components, may also affect other cellular functions, ...resulting in potential comorbidity effects. By combining information on cellular interactions, disease‐‐gene associations, and population‐level disease patterns extracted from Medicare data, we find statistically significant correlations between the underlying structure of cellular networks and disease comorbidity patterns in the human population. Our results indicate that such a combination of population‐level data and cellular network information could help build novel hypotheses about disease mechanisms.
Cellular ingredient concentrations can be stabilized by adjusting generation and consumption rates through multiple pathways. To explore the portion of cellular metabolism equipped with multiple ...pathways, we categorize individual metabolic reactions and compounds as viable or inviable: A compound is viable if processed by two or more reactions, and a reaction is viable if all of its substrates and products are viable. Using this classification, we identify the maximal subnetwork of viable nodes, referred to as the viable core, in bipartite metabolic networks across thousands of species. The obtained viable cores are remarkably larger than those in degree-preserving randomized networks, while their broad degree distributions commonly enable the viable cores to shrink gradually as reaction nodes are deleted. We demonstrate by investigating the viable cores and the branching ratios of inviable nodes in the pruning process for artificial correlated networks that the positive degree–degree correlations of the empirical networks may underlie the enlarged viable cores compared to the randomized networks. By investigating the relation between degree and cross-species frequency of metabolic compounds and reactions, we elucidate the evolutionary origin of the correlations. Our study unveils the principle of metabolic resource allocation and its evolutionary mechanism, potentially useful for pharmaceutical applications.
•Structurally defining viable cores of metabolism.•Finding the enhanced empirical cores than expected against perturbations.•Analyzing the positive degree–degree correlation effects on the enlarged cores.
Different shares of distinct commodity sectors in production, trade, and consumption illustrate how resources and capital are allocated and invested. Economic progress has been claimed to change the ...share distribution in a universal manner as exemplified by the Engel's law for the household expenditure and the shift from primary to manufacturing and service sector in the three sector model. Searching for large-scale quantitative evidence of such correlation, we analyze the gross-domestic product (GDP) and international trade data based on the standard international trade classification (SITC) in the period 1962 to 2000. Three categories, among ten in the SITC, are found to have their export shares significantly correlated with the GDP over countries and time; The machinery category has positive and food and crude materials have negative correlations. The export shares of commodity categories of a country are related to its GDP by a power-law with the exponents characterizing the GDP-elasticity of their export shares. The distance between two countries in terms of their export portfolios is measured to identify several clusters of countries sharing similar portfolios in 1962 and 2000. We show that the countries whose GDP is increased significantly in the period are likely to transit to the clusters displaying large share of the machinery category.
The spatial distributions of diverse facilities are often understood in terms of the optimization of the commute distance or the economic profit. Incorporating more general objective functions into ...such optimization framework may be useful, helping the policy decisions to meet various social and economic demands. As an example, we consider how hospitals should be distributed to minimize the total fatalities of tuberculosis (TB). The empirical data of Korea shows that the fatality rate of TB in a district decreases with the areal density of hospitals, implying their correlation and the possibility of reducing the nationwide fatalities by adjusting the hospital distribution across districts. Approximating the fatality rate by the probability of a patient not to visit a hospital in her/his residential district for the duration period of TB and evaluating the latter probability in the random-walk framework, we obtain the fatality rate as an exponential function of the hospital density with a characteristic constant related to each district's effective lattice constant estimable empirically. This leads us to the optimal hospital distribution which finds the hospital density in a district to be a logarithmic function of the rescaled patient density. The total fatalities is reduced by 13% with this optimum. The current hospital density deviates from the optimized one in different manners from district to district, which is analyzed in the proposed model framework. The assumptions and limitations of our study are also discussed.
The prevalence of wealth inequality propels us to characterize its origin and progression via empirical and theoretical studies. The yard-sale (YS) model, in which a portion of the smaller wealth is ...transferred between two individuals, culminates in the concentration of almost all wealth to a single individual, while distributing the rest of the wealth with a power law of exponent one. By incorporating redistribution to the model, in which the transferred wealth is proportional to the sender's wealth, we show that such extreme inequality is suppressed if the frequency ratio of redistribution to the YS-type exchange exceeds the inverse of the population size. Studying our model on a sparsely-connected population, we find that the wealth inequality ceases to grow for a period, when local rich nodes can no longer acquire wealth from their broke nearest neighbors. Subsequently, inequality resumes growth due to the redistribution effect by allowing locally amassed wealth to move and coalesce. Analyzing the Langevin equations and the coalescing random walk on complex networks, we elucidate the scaling behaviors of wealth inequality in those multiple phases. These findings reveal the influence of network structure on wealth distribution, offering a novel perspective on wealth inequality.
We study the synchronization transition in scale-free networks that display power-law asymptotic behaviors in their degree distributions. The critical coupling strength and the order-parameter ...critical exponent derived by the mean-field approach depend on the degree exponent lambda, which implies a close connection between structural organization and the emergence of dynamical order in complex systems. We also derive the finite-size scaling behavior of the order parameter, finding that the giant cluster of synchronized nodes is formed in different ways between scale-free networks with 2 < lambda < 3 and those with lambda > 3.
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