Identifying regulation with adversarial surrogates.

Homeostasis, the ability to maintain a relatively constant internal environment in the face of perturbations, is a hallmark of biological systems. It is believed that this constancy is achieved through multiple internal regulation and control processes. Given observations of a system, or even a detailed model of one, it is both valuable and extremely challenging to extract the control objectives of the homeostatic mechanisms. In this work, we develop a robust data-driven method to identify these objectives, namely to understand: "what does the system care about?". We propose an algorithm, Identifying Regulation with Adversarial Surrogates (IRAS), that receives an array of temporal measurements of the system and outputs a candidate for the control objective, expressed as a combination of observed variables. IRAS is an iterative algorithm consisting of two competing players. The first player, realized by an artificial deep neural network, aims to minimize a measure of invariance we refer to as the coefficient of regulation. The second player aims to render the task of the first player more difficult by forcing it to extract information about the temporal structure of the data, which is absent from similar "surrogate" data. We test the algorithm on four synthetic and one natural data set, demonstrating excellent empirical results. Interestingly, our approach can also be used to extract conserved quantities, e.g., energy and momentum, in purely physical systems, as we demonstrate empirically.

Modeling the Impact of Proportion, Sowing Date, and Architectural Traits of a Companion Crop on Foliar Fungal Pathogens of Wheat in Crop Mixtures.

Diversification of cropping systems is a lever for the management of epidemics. However, most research to date has focused on cultivar mixtures, especially for cereals, even though crop mixtures can also improve disease management. To investigate the benefits of crop mixtures, we studied the effect of different crop mixture characteristics (i.e., companion proportion, sowing date, and traits) on the protective effect of the mixture. We developed a SEIR (Susceptible, Exposed, Infectious, Removed) model of two damaging wheat diseases (Zymoseptoria tritici and Puccinia triticina), which were applied to different canopy components, ascribable to wheat and a theoretical companion crop. We used the model to study the sensitivity of disease intensity to the following parameters: wheat-versus-companion proportion, companion sowing date and growth, and architectural traits. For both pathogens, the companion proportion had the strongest effect, with 25% of companion reducing disease severity by 50%. However, changing companion growth and architectural traits also significantly improved the protective effect. The effect of companion characteristics was consistent across different weather conditions. After decomposing the dilution and barrier effects, the model suggested that the barrier effect is maximized for an intermediate proportion of companion crop. Our study thus supports crop mixtures as a promising strategy to improve disease management. Future studies should identify real species and determine the combination of host and companion traits to maximize the protective effect of the mixture. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A critical analysis on the conception of "Pre-existent gene expression programs" for cell differentiation and development.

A pre-existent gene expression program at the basis of cell differentiation and development is often assumed in the current scientific literature. Historically this conception is traced to the nineteen sixties of the last century, when various influential papers and scientific personalities imprinted their view drawing inspiration from informatics. The accepted model is that in the presence of certain external and/or internal signals, a cell initiates a pre-determined program of gene expression by which it becomes differentiated. Authors generally do not question the evidence for the existence of such a program. Here I review different aspects and consequences of this model to conclude that it is completely at odds with the literature of the last decades, which has given us a splendid view of the dynamics of the living cell as an auto-organizing complex unit that is far away from thermodynamical equilibrium. In this view there is no place for programs.

Synchronization between Attractors: Genomic Mechanism of Cell-Fate Change.

Herein, we provide a brief overview of complex systems theory approaches to investigate the genomic mechanism of cell-fate changes. Cell trajectories across the epigenetic landscape, whether in development, environmental responses, or disease progression, are controlled by extensively coordinated genome-wide gene expression changes. The elucidation of the mechanisms underlying these coherent expression changes is of fundamental importance in cell biology and for paving the road to new therapeutic approaches. In previous studies, we pointed at dynamic criticality as a plausible characteristic of genome-wide transition dynamics guiding cell fate. Whole-genome expression develops an engine-like organization (genome engine) in order to establish an autonomous dynamical system, capable of both homeostasis and transition behaviors. A critical set of genes behaves as a critical point (CP) that serves as the organizing center of cell-fate change. When the system is pushed away from homeostasis, the state change that occurs at the CP makes local perturbation spread over the genome, demonstrating self-organized critical (SOC) control of genome expression. Oscillating-Mode genes (which normally keep genome expression on pace with microenvironment fluctuations), when in the presence of an effective perturbative stimulus, drive the dynamics of synchronization, and thus guide the cell-fate transition.

Variable metabolic scaling breaks the law: from 'Newtonian' to 'Darwinian' approaches.

Life's size and tempo are intimately linked. The rate of metabolism varies with body mass in remarkably regular ways that can often be described by a simple power function, where the scaling exponent (b, slope in a log-linear plot) is typically less than 1. Traditional theory based on physical constraints has assumed that b is 2/3 or 3/4, following natural law, but hundreds of studies have documented extensive, systematic variation in b. This overwhelming, law-breaking, empirical evidence is causing a paradigm shift in metabolic scaling theory and methodology from 'Newtonian' to 'Darwinian' approaches. A new wave of studies focuses on the adaptable regulation and evolution of metabolic scaling, as influenced by diverse intrinsic and extrinsic factors, according to multiple context-dependent mechanisms, and within boundary limits set by physical constraints.

Consecutive feedback-driven constitutional dynamic networks.

Cellular transformations are driven by environmentally triggered complex dynamic networks, which include signal-triggered feedback processes, cascaded reactions, and switchable transformations. We apply the structural and functional information encoded in the sequences of nucleic acids to construct signal-triggered constitutional dynamic networks (CDNs) that mimic the functions of natural networks. Using predesigned hairpin structures as triggers, the network generates functional strands, which stabilize one or the other of the constituents of the network, leading to feedback-driven reconfiguration and time-dependent equilibration of the networks. Using structurally designed hairpins, positive-feedback or negative-feedback mechanisms operated by the CDNs are demonstrated. With two predesigned hairpins, the coupled consecutive operations of negative/positive- or positive/positive- feedback cascades are accomplished. The time-dependent composition changes of the networks are well reproduced by chemical kinetics simulations that provide predictive behaviors of the network, under variable auxiliary conditions. Beyond mimicking natural network properties and functions by means of the synthetic nucleic-acid-based CDNs, the systems introduce versatile perspectives for the design of amplified sensors (sensing of miRNA-376a) and the development of logic gate circuits.

On Computing Structural and Behavioral Complexities of Threshold Boolean Networks : Application to Biological Networks.

Various threshold Boolean networks (TBNs), a formalism used to model different types of biological networks (genes notably), can produce similar dynamics, i.e. share same behaviors. Among them, some are complex (according to Kolmogorov complexity), others not. By computing both structural and behavioral complexities, we show that most TBNs are structurally complex, even those having simple behaviors. For this purpose, we developed a new method to compute the structural complexity of a TBN based on estimates of the sizes of equivalence classes of the threshold Boolean functions composing the TBN.

Cell-Fate Determination from Embryo to Cancer Development: Genomic Mechanism Elucidated.

Elucidation of the genomic mechanism that guides the cell-fate change is one of the fundamental issues of biology. We previously demonstrated that whole genome expression is coordinated by the emergence of a critical point at both the cell-population and single-cell levels through the physical principle of self-organized criticality. In this paper, we further examine the genomic mechanism that determines the cell-fate changes from embryo to cancer development. The state of the critical point, acting as the organizing center of the cell fate, determines whether the genome resides in a super- or sub-critical state. In the super-critical state, a specific stochastic perturbation can spread over the entire system through the "genome engine", an autonomous critical-control genomic system, whereas in the sub-critical state, the perturbation remains at a local level. The cell-fate changes when the genome becomes super-critical. We provide a consistent framework to develop a time-evolutional transition theory for the biological regulation of the cell-fate change.

Illumina sequencing revealed roles of microRNAs in different aluminum tolerance of two citrus species.

Self-germinated seedlings of Citrus sinensis and C. grandis were supplied with nutrient solution with 0 mM AlCl3·6H2O (control, -Al) or 1 mM AlCl3·6H2O (+Al) for 18 weeks. The DW (Dry weights) of leaf, stem, shoot and the whole plant of C. grandis were decreased and the ratio of root DW to shoot DW in C. grandis were increased by Al, whereas these parameters of C. sinensis were not changed by Al. Al treatment dramatically decreased the sulfur (S) content in C. grandis roots and the phosphorus (P) content in both C. sinensis and C. grandis roots. More Al was transported to shoots and leaves in C. grandis than in C. sinensis under Al treatment. Al treatment has more adverse effects on C. grandis than on C. sinensis, as revealed by the higher production of superoxide anion (O2 ·-), H2O2 and thiobarbituric acid reactive substace (TBARS) content in C. grandis roots. Via the Illumina sequencing technique, we successfully identified and quantified 12 and 16 differentially expressed miRNAs responding to Al stress in C. sinensis and C. grandis roots, respectively. The possible mechanism underlying different Al tolerance of C. sinensis and C. grandis were summarized as having following aspects: (a) enhancement of adventitious and lateral root development (miR160); (b) up-regulation of stress and signaling transduction related genes, such as SGT1, PLC and AAO (miR477, miR397 and miR398); (c) enhancement of citrate secretion (miR3627); (d) more flexible control of alternative glycolysis pathway and TCA cycle (miR3627 and miR482); (e) up-regulation of S-metabolism (miR172); (f) more flexible control of miRNA metabolism. For the first time, we showed that root development (miR160) and cell wall components (cas-miR5139, csi-miR12105) may play crucial roles in Al tolerance in citrus plants. In conclusion, our study provided a comprehensive profile of differentially expressed miRNAs in response to Al stress between two citrus plants differing in Al tolerance which further enriched our understanding of the molecular mechanism underlying Al tolerance in plants.

Design principles for the analysis and construction of robustly homeostatic biological networks.

Homeostatic biological systems resist external disturbances, allowing cells and organisms to maintain a constant internal state despite perturbations from their surroundings. Many biological regulatory networks are known to act homeostatically, with examples including thermal adaptation, osmoregulation, and chemotaxis. Understanding the network topologies (sets of regulatory interactions) and biological parameter regimes that can yield homeostasis in a biological system is of interest both for the study of natural biological system, and in the context of designing new biological control schemes for use in synthetic biology. Here, we examine the mathematical properties of a function that maps a biological system's inputs to its outputs, we have formulated a novel criterion (the "cofactor condition") that compactly describes the conditions for homeostasis. We further analyze the problem of robust homeostasis, wherein the system is required to maintain homeostatic behavior when its parameter values are slightly altered. We use the cofactor condition to examine previously reported examples of robust homeostasis, showing that it is a useful way to unify a number of seemingly different analyses into a single framework. Based on the observation that all previous robustly homeostatic examples fall into one of three classes, we propose a "strong cofactor condition" and use it to provide an algorithm for designing new robustly homeostatic biological networks, giving both their topologies and constraints on their parameter values. Applying the design algorithm to a three-node biological network, we construct several robustly homeostatic genetic networks, uncovering network topologies not previously identified as candidates for exhibiting robust homeostasis.

From Cell States to Cell Fates: Control of Cell State Transitions.

We examine the coordinated behavior of thousands of genes in cell fate transitions through genome expression as an integrated dynamical system using the concepts of self-organized criticality and coherent stochastic behavior. To quantify the effects of the collective behavior of genes, we adopted the flux balance approach and developed it in a new tool termed expression flux analysis (EFA). Here we describe this tool and demonstrate how its application to specific experimental genome-wide expression data provides new insights into the dynamics of the cell-fate transitions. Particularly, we show that in cell fate change, specific stochastic perturbations can spread over the entire system to guide distinct cell fate transitions through switching cyclic flux flow in the genome engine. Utilization of EFA enables us to elucidate a unified genomic mechanism for when and how cell-fate change occurs through critical transitions.

Regulating the biodegradation of petroleum hydrocarbons with different carbon chain structures by composting systems.

Composting can decrease petroleum hydrocarbons in petroleum contaminated soils, however the microbial degradation mechanisms and regulating method for biodegradation of petroleum hydrocarbons with different carbon chain structures in the composting system have not yet been investigated. This study analyzed variations of total petroleum hydrocarbon concentrations with C ≤ 16 and C > 16, Random Forest model was applied to identify the key microorganisms for degrading the petroleum hydrocarbon components with specific structure in biomass-amended composting. Regulating method for biodegradation of petroleum hydrocarbons with different carbon chain structures was proposed by constructing the influence paths of "environmental factors-key microorganisms- total petroleum hydrocarbons". The results showed that composting improved the degradation rate of C ≤ 16 fraction and C > 16 fraction of petroleum hydrocarbons by 67.88 % and 61.87 %, respectively. Analysis of the microbial results showed that the degrading bacteria of the C ≤ 16 fraction had degradation advantages in the heating phase of the compost, while the C > 16 fraction degraded better in the cooling phase. Moreover, microorganisms that specifically degraded C > 16 fractions were significantly associated with total nitrogen and nitrate nitrogen. The biodegradation of C ≤ 16 fraction was regulated by organic matter, moisture content, and temperature. The composting system modified by biogas slurry was effective in removing of petroleum hydrocarbons with different carbon chain structures in soil by regulating the metabolic potential of the 46 key microorganisms. This study given their expected importance to achieve the purpose of treating waste with waste and contributing to soil utilization as well as pollution remediation.

Generic model for biological regulation.

A substantial portion of molecules in an organism are involved in regulation of a wide spectrum of biological processes. Several models have been presented for various forms of biological regulation, including gene expression regulation and physiological regulation; however, a generic model is missing. Recently a new unifying theory in biology, poikilosis, was presented.  Poikilosis indicates that all systems display intrinsic heterogeneity. The concept of poikilosis allowed development of a model for biological regulation applicable to all types of regulated systems. The perturbation-lagom-TATAR countermeasures-regulator (PLTR) model combines the effects of perturbation and lagom (allowed and sufficient extent of heterogeneity) in a system with tolerance, avoidance, repair, attenuation and resistance (TARAR) countermeasures, and possible regulators. There are three modes of regulation, two of which are lagom-related. In the first scenario, lagom is maintained, both intrinsic (passive) and active TARAR countermeasures can be involved. In the second mode, there is a shift from one lagom to another. In the third mode, reguland regulation, the regulated entity is the target of a regulatory shift, which is often irreversible or requires action of another regulator to return to original state. After the shift, the system enters to lagom maintenance mode, but at new lagom extent. The model is described and elaborated with examples and applications, including medicine and systems biology. Consequences of non-lagom extent of heterogeneity are introduced, along with a novel idea for therapy by reconstituting biological processes to lagom extent, even when the primary effect cannot be treated.

The anabolism of sulphur aroma volatiles responds to enzymatic and non-enzymatic reactions during the drying process of shiitake mushrooms.

The anabolism of aroma volatiles in response to non-biological factors during the drying process of shiitake mushrooms was analyzed. Temperatures (40 °C, 50 °C, and 60 °C) had secondary activation effects on the synthetase activity. The enzymatic reaction time could last 4-5 h under medium-temperature drying process (40 °C and 50 °C), and 1.5-2 h under a high-temperature drying process (60 °C and 70 °C). The aroma synthesis dominated by non-enzymatic reactions were chemical reactions between amino acids and reducing sugars. The hot-air drying process of shiitake mushroom was consistent with the cubic model and the key control points influencing the enzymatic reaction parameters were in the order of moisture rate > temperature > drying time > drying rate. The non-enzymatic reaction parameters were in the order of temperature > drying time > drying rate > moisture rate. The total sulfur volatiles produced in the optimized process were significantly higher, and the drying time of the process could be completed within 6 h.

Eco-chemical mechanisms govern phytoplankton emissions of dimethylsulfide in global surface waters.

The anti-greenhouse gas dimethylsulfide (DMS) is mainly emitted by algae and accounts for more than half of the total natural flux of gaseous sulfur to the atmosphere, strongly reducing the solar radiation and thereby the temperature on Earth. However, the relationship between phytoplankton biomass and DMS emissions is debated and inconclusive. Our study presents field observations from 100 freshwater lakes, in concert with data of global ocean DMS emissions, showing that DMS and algal biomass show a hump-shaped relationship, i.e. DMS emissions to the atmosphere increase up to a pH of about 8.1 but, at higher pH, DMS concentrations decline, likely mainly due to decomposition. Our findings from lake and ocean ecosystems worldwide were corroborated in experimental studies. This novel finding allows assessments of more accurate global patterns of DMS emissions and advances our knowledge on the negative feedback regulation of phytoplankton-driven DMS emissions on climate.

Grassland production in response to changes in biological metrics over the Tibetan Plateau.

A clear interannual variability in annual production of grasslands (termed AEVI) has been reported over the Tibetan Plateau (TP), but the underlying mechanism has not been fully understood. Here, we explained the interannual variability of AEVI during 2001-2015 by two phenological metrics (the start and end of the growing season, termed SOS and EOS, respectively) and one physiological metric (the maximum capacity of canopy light absorbance, termed MEVI) using MODIS Enhanced Vegetation Index (EVI) data over the TP. The results showed that the interannual variability of AEVI can be well attributed to not only the trends of, but also the sensitivities of AEVI to, the selected biological metrics. On the one hand, the advancing SOS and delaying EOS dominated the study area while both increased and decreased MEVI were observed. On the other hand, the AEVI responded negatively to the SOS and positively to the EOS and MEVI, exhibiting significant variations along the temperature and precipitation gradients. Hence, the current interannual variability of SOS and EOS mainly increased the AEVI; meanwhile, both enhancement and suppression of the interannual variability of MEVI to the AEVI were widespread over the TP. Overall, the interannual variability of MEVI mostly contributed to that of the AEVI, indicating a dominant role of the physiological metric rather than phenological metrics in carbon gain of TP grasslands. The achievements of this study are helpful to understand the underlying biological causes of the interannual variability of grassland production over the TP.

The Search for System's Parameters.

The analysis of biological data asks for a delicate balance of content-specific and procedural knowledge; this is why it is virtually impossible to apply standard mathematical and statistical recipes to systems biology.The separation of the important part of information from singular (and largely irrelevant) details implies a continuous interchange between biological and statistical knowledge. The generalization ability of the models must be the principal focus of system's parameter estimation, while the multi-scale character of biological regulation orients the modeling style toward data-driven strategies based on the correlation structure of the analyzed systems.

The Bioactivity of D-/L-Isonucleoside- and 2'-Deoxyinosine-Incorporated Aptamer AS1411s Including DNA Replication/MicroRNA Expression.

In this study, chemical modification of 2'-deoxyinosine (2'-dI) and D-/L-isothymidine (D-/L-isoT) was performed on AS1411. They could promote the nucleotide-protein interaction by changing the local conformation. Twenty modified sequences were obtained, FCL-I and FCL-II showed the most noticeable activity improvement. They stabilized the G-quadruplex, remained highly resistant to serum degradation and specificity for nucleolin, further inhibited tumor cell growth, exhibited a stronger ability to influence the different phases of the tumor cell cycle, induced S-phase arrest, promoted the inhibition of DNA replication, and suppressed the unwound function of a large T antigen as powerful as AS1411. The microarray analysis and TaqMan PCR results showed that FCL-II can upregulate the expression of four breast-cancer-related, lowly expressed miRNAs and downregulate the expression of three breast-cancer-related, highly expressed miRNAs (>2.5-fold). FCL-II resulted in enhanced treatment effects greater than AS1411 in animal experiments (p < 0.01). The computational results further proved that FCL-II exhibits more structural advantages than AS1411 for binding to the target protein nucleolin, indicating its great potential in antitumor therapy.

Influence of microbial consortia on the incidence of grey mold (Botrytis cinerea) in strawberry (Monterey variety)

Botrytis cinerea, the causal agent of grey mold disease, is one of the most destructive pathogens of strawberry crops, both in vegetative development and postharvest. The control of this pathogen is complex due to its aggressiveness and ability to attack and infect various plant tissues and is mainly based on chemical control; however, the incorrect use of pesticides, mainly due to overdosing, causes the presence of traces of these agrochemicals in the fruits, as well as the selection of pathogen resistance to fungicides, making it a risk to human health and the environment. The objective of the study was to use biological regulation strategies, with the application of microbial consortia made up of mycorrhizal fungi, antagonistic bacteria and Trichoderma harzianum, as an alternative for the management of grey mold in strawberry crops (Monterey variety) under field conditions. Treatments T4 (mycorrhizal fungi), T8 (mycorrhizal fungi, antagonistic bacteria and T. harzianum) and T2 (T. harzianum) presented the lowest incidence of the pathogen with 2.6, 3.1 and 3.6 %, respectively, compared to control plants with 16.6%. The influence of all biological treatments on the regulation of B. cinerea was greater than the control.

Botrytis cinerea, el agente causal de la enfermedad del moho gris, es uno de los patógenos más destructivos del cultivo de fresa, tanto en el desarrollo vegetativo como en poscosecha. El control de este patógeno es complejo, debido a su agresividad y capacidad de atacar e infectar diversos tejidos de la planta y se basa, principalmente, en el control químico; sin embargo, el uso incorrecto de plaguicidas, principalmente por sobredosificación, provoca la presencia de trazas de estos agroquímicos en los frutos, así como la selección de resistencia del patógeno a los fungicidas, convirtiéndolo en un riesgo para la salud humana y el ambiente. El objetivo del estudio fue utilizar estrategias de regulación biológica, con la aplicación de consorcios microbianos, conformados por hongos micorrícicos, bacterias antagonistas y Trichoderma harzianum, como alternativa para el manejo del moho gris, en cultivos de fresa (variedad Monterey), en condiciones de campo. Los tratamientos T4 (hongos micorrízicos), T8 (hongos micorrízicos, bacterias antagonistas y T. harzianum) y T2 (T. harzianum) presentaron la menor incidencia del patógeno, con 2,6, 3,1 y 3,6 %, respectivamente, en comparación con las plantas control, con 16,6 %. La influencia de todos los tratamientos biológicos en la regulación de B. cinerea fue mayor respecto al control.

Bioelectronic light-gated transistors with biologically tunable performance.

Light-activated bioelectronic silicon nanowire transistor devices are made by fusing proteoliposomes containing a bacteriorhodopsin (bR) proton pump onto the nanowire surface. Under green-light illumination, bR pumps protons toward the nanowire, and the pH gradient developed by the pump changes the transistor output. Furthermore, co-assembly of small biomolecules that alter the bilayer permeability to other ions can upregulate and downregulate the response of field-effect transistor devices.