Bioremediation can help reduce and remove the pollution we produce, to provide clean air, water, and healthy soils for future generations. Pollution damages our health and the environment, affecting wildlife and the sustainability of our planet, as summarised in our policy briefing on food security. Under controlled conditions, bioremediation is the process of biologically degrading organic wastes, typically to a state of innocuousness or to concentration levels that remain within particular concentration limits set forth by the controlling authority. In bioremediation, it is possible to do it either ex situ or in situ, depending on a number of factors, such as the type and concentration of pollutants, cost, and/or site characteristics. As a result, ex situ is generally more expensive than in situ, since excavation results in additional expenses. Biological processes are the most effective and economical way to remediate a polluted site. Though bioremediation is not a new technique, our understanding of the mechanisms behind it is growing, enabling us to use it more effectively. Frequently, bioremediation uses fewer resources and less energy than conventional technologies and doesn't produce waste products that can be hazardous bioremediation has both technical and cost advantages, though it can sometimes take longer to complete than traditional methods. © 2024 selection and editorial matter, Pratibha Gautam, Vineet Kumar and Sunil Kumar; individual chapters, the contributors.

Large groups of active cilia collectively beat in a fluid medium as metachronal waves, essential for some microorganisms motility and for flow generation in mucociliary clearance. Several models can predict the emergence of metachronal waves, but what controls the properties of metachronal waves is still unclear. Here, we numerically investigate the respective impacts of active beating and viscous dissipation on the properties of metachronal waves in a collection of oscillators, using a simple model for cilia in the presence of noise on regular lattices in one and two dimensions. We characterize the wave using spatial correlation and the frequency of collective beating. Our results clearly show that the viscosity of the fluid medium does not affect the wavelength; the activity of the cilia does. These numerical results are supported by a dimensional analysis, which shows that the result of wavelength invariance is robust against the model taken for sustained beating and the structure of hydrodynamic coupling. Interestingly, the enhancement of cilia activity increases the wavelength and decreases the beating frequency, keeping the wave velocity almost unchanged. These results might have significance in understanding paramecium locomotion and mucociliary clearance diseases. © 2024 American Physical Society.

Expressed gene products often interact ubiquitously with binding sites at nucleic acids and macromolecular complexes, known as decoys. The binding of transcription factors (TFs) to decoys can be crucial in controlling the stochastic dynamics of gene expression. Here, we explore the impact of decoys on the timing of intracellular events, as captured by the time taken for the levels of a given TF to reach a critical threshold level, known as the first passage time (FPT). Although nonlinearity introduced by binding makes exact mathematical analysis challenging, employing suitable approximations and reformulating FPT in terms of an alternative variable, we analytically assess the impact of decoys. The stability of the decoy-bound TFs against degradation impacts FPT statistics crucially. Decoys reduce noise in FPT, and stable decoy-bound TFs offer greater timing precision with less expression cost than their unstable counterparts. Interestingly, when both bound and free TFs decay at the same rate, decoy binding does not directly alter FPT noise. We verify these results by performing exact stochastic simulations. These results have important implications for the precise temporal scheduling of events involved in the functioning of biomolecular clocks, development processes, cell-cycle control, and cell-size homeostasis

Expressed Transcription Factors (TFs) not only bind to sites at target promoters but also to decoy sites scattered across the genome. Binding to such “decoys” sequesters TFs critically impacting the response time and stochasticity (noise) in TF and target gene expression level. When the TF is a stable molecule, whose concentration is diluted by cellular growth, our results show that for fixed mean concentration levels, such decoy bindings can both enhance or suppress random fluctuations in TF levels depending on the source of noise (i.e., intrinsic vs. extrinsic noise) and the strength of binding (i.e., weak vs. strong decoys). We implement negative autoregulation where free (unbound) TF molecules inhibit their synthesis. Our analytical results corroborated by numerical simulations reveal that sequestration accentuates the effects of feedback in the sense that noise attenuation by negative feedback is higher with sequestration than in the absence of feedback. We next consider an alternative form of feedback where the TF increases the production of its decoys, and such feedback architectures are frequently seen in endogenous gene regulation involving microRNA-TF circuits and in controlling cellular stress responses. For these circuits where decoy numbers are TF-regulated, we identify limits of noise suppression, and in many cases, these limits occur at intermediate TF-decoy binding affinities.

Timely progression of a genetic program is critical for embryonic development. However, gene expression involves inevitable fluctuations in biochemical reactions leading to substantial cell-to-cell variability (gene expression noise). One of the important questions in developmental biology is how pattern formation is reproducibly executed despite these unavoidable fluctuations in gene expression. Here, we studied the transcriptional variability of two paired zebrafish segmentation clock genes ( her1 and her7 ) in multiple genetic backgrounds. Segmentation clock genes establish an oscillating self-regulatory system, presenting a challenging yet beautiful system in studying control of transcription variability. In this study, we found that a negative feedback loop established by the Her1 and Her7 proteins minimizes uncorrelated variability whereas gene copy number affects variability of both RNAs in a similar manner (correlated variability). We anticipate that these findings will help analyze the precision of other natural clocks and inspire the ideas for engineering precise synthetic clocks in tissue engineering.

The abundance of specific protein molecules in genetically identical cell populations exposed to the same external environment can show remarkable cell-to-cell variations as biochemical reactions are inherently stochastic and occur with low numbers of molecular copies. Such variations in gene products are commonly known as gene expression noise. One of the mechanisms for cells to reduce such noise is auto-regulatory negative feedback (auto-inhibition), commonly found across organisms. This auto-inhibition is subjected to unavoidable time-delays associated with transcriptional and translational processes. Sufficient time-delays and strong auto-inhibition can generate sustained oscillations in gene products, which is a common mechanism for precise timekeeping in many biomolecular clocks. While the importance of time-delays in the generation of oscillations is well appreciated, its role in stochastic dynamics is not well understood in the absence of sustained oscillations. Here, we investigate the interplay between the feedback strength and the time-delay to study the noise propagation in the non-oscillatory regime using linear stability analysis, the linear noise approximation, and stochastic simulations. From a simple auto-regulatory model with one protein species (no delay), we systematically introduce one-step and two-step time-delays by incorporating intermediate dynamics with additional second and third species, respectively. Interestingly, the negative feedback in the presence of time-delay can show counterintuitive noise behavior to our common perception about its role as a noise buffer.

Nonlinear feedback controllers are ubiquitous features of biological systems at different scales. A key motif arising in these systems is sequestration-based feedback. As a physiological example of this type of feedback architecture, platelets (specialized cells involved in blood clotting) differentiate from stem cells, and this process is activated by a protein called Thrombopoietin (TPO). Platelets actively sequester and degrade TPO, creating negative feedback whereby any depletion of platelets increases the levels of freely available TPO that upregulates platelet production. We show similar examples of sequestration-based feedback in intracellular biomolecular circuits involved in heat-shock response and microRNA regulation. Our systematic analysis of this feedback motif reveals that platelets-induced degradation of TPO is critical in enhancing system robustness to external disturbances. In contrast, reversible sequestration of TPO without degradation results in poor robustness to disturbances. We develop exact analytical results quantifying the limits to which the sensitivity to disturbances can be attenuated by sequestration-based feedback. In summary, our systematic analysis highlights design principles for enhancing the robustness of sequestration-based feedback mechanisms to external disturbances with applications to both physiological and cellular systems.

Within cells, transcription factors (TFs) bind to a wide range of nonspecific genomic sites in addition to their target sites. Binding to such high affinity “decoys” has been shown to qualitatively alter the dynamics of gene regulatory circuits. Analyzing simple gene expression models with decoy binding we derive formulas for the TF response time as a function of the number of decoys, binding affinity, and stability of the decoy-bound TF. Our results show that while on one hand, decoys make the response sluggish whenever decoy binding stabilizes the TF, on the other hand, decoys can accelerate responses by destabilizing the bound TF. We apply these results in the context of a genetic oscillator based on an activator-repressor motif, where sustained oscillations result from a rapid activator-mediated positive feedback working in conjunction with a slow repressor-mediated negative feedback. Consistent with our response time analysis, we find that activator binding to decoy sites can destroy oscillations in the case of a stable decoy-activator complex that functions to slow down the positive feedback. In contrast, an unstable decoy-activator complex can expand the oscillatory parameter regime. In conclusion, our response time analysis provides intuitive insights into the emergence of sustained oscillations.