Daniel Giraldez Guerra

The Mycobacterium tuberculosis RNA polymerase (MtbRNAP) is the target of the first-line anti-tuberculosis inhibitor rifampin, however, the emergence of rifampin resistance necessitates the development of new antibiotics. Here, we communicate the first single-molecule characterization of MtbRNAP elongation and its inhibition by three diverse small-molecule inhibitors: N(α)-aroyl-N-aryl-phenylalaninamide (D-IX216), streptolydigin (Stl), and pseudouridimycin (PUM) using high-resolution optical tweezers. Compared to Escherichia coli RNA polymerase (EcoRNAP), MtbRNAP transcribes more slowly, has similar mechanical robustness, and only weakly recognizes E. coli pause sequences. The three small-molecule inhibitors of MtbRNAP exhibit strikingly different effects on transcription elongation. In the presence of D-IX216, which inhibits RNAP active-center bridge-helix motions required for nucleotide addition, the enzyme exhibits transitions between slowly and super-slowly elongating inhibited states. Stl, which inhibits the RNAP trigger-loop motions also required for nucleotide addition, inhibits RNAP primarily by inducing pausing and backtracking. PUM, a nucleoside analog of UTP, in addition to acting as a competitive inhibitor, induces the formation of slowly elongating RNAP inhibited states. Our results indicate that the three classes of small-molecule inhibitors affect the enzyme in distinct ways and show that the combination of Stl and D-IX216, which both target the RNAP bridge helix, has a strong synergistic effect on the enzyme.

Whole-cell biosensors detecting the heavy metal arsenic have been widely studied for their potential in environmental monitoring. And while inducible biosensors have been shown to be an effective tool to tune the operational range, a thoroughly characterised inducible biosensor is currently lacking. Here, we present an Escherichia coli biosensor for arsenic in which the transcription factor gene arsR is inducible by naringenin, a plant-derived secondary metabolite. Increasing naringenin concentrations reduced the basal output while increasing both the dynamic range and sensing threshold of the biosensor dose-response curves, but the operational ranges appeared constrained by a fixed upper limit. Comparison with a previously published phenomenological model revealed good overall agreement between experimental data and model predictions, except for the behaviour of the maximum output and threshold. This work expands the biosensor toolbox with a profoundly characterised arsenic biosensor and raises a potential practical limit to dose-response curve engineering by tuning transcription factor expression alone. Graphical

Whole-cell biosensors (WCBs) are instrumental platforms for discovering and characterizing regulatory elements and advancing bioengineering. They also hold immense promise for environmental and food monitoring. While significant efforts have been invested in enhancing their sensitivity and portability, the standardization of their handling and data analysis remains relatively underdeveloped. This article presents a comprehensive guide to utilizing two recently developed WCBs, Mer-Blue and Mer-RFP, proven capable of detecting ionic mercury at levels below the World Health Organization's drinking water limits. The protocols detailed herein encompass microbial culture preparation, sensor calibration, data acquisition, and analysis. For the fluorometric Mer-RFP biosensor, a novel biosynthesis allocation theorem is employed to identify the time interval for reliable and accurate dose-response measurements. For the colorimetric Mer-Blue biosensor, a low-cost camera setup enables rigorous measurements in settings lacking expensive spectrophotometers and fluorimeters, facilitating decentralized pollution monitoring. The procedures used for testing freshwater samples are described, and the limitations of these biosensors with respect to sample types are discussed. By sharing these handling and analysis techniques, we encourage broader research groups to adopt and improve these biological devices for developing effective environmental monitoring solutions. Ultimately, this research aims to facilitate the widespread adoption of biosensor technologies within the environmental science community, contributing to more effective and efficient monitoring of trace element pollution in various ecosystems.

Many studies characterize transcription factors and other regulatory elements to control gene expression in recombinant systems. However, most lack a formal approach to analyse the inherent and context-specific variations of these regulatory components. This study addresses this gap by establishing a formal framework from which convenient methods are inferred to characterize regulatory circuits. We modelled the bacterial cell as a collection of proteome fractions. Deriving the time-dependent proteome fraction, we obtained a general theorem that describes its change as a function of its expression fraction, a specific portion of the total biosynthesis flux of the cell. Formal deduction reveals that when the proteome fraction reaches a maximum, it becomes equivalent to its expression fraction. This equation enables the reliable measurement of the expression fraction through direct protein quantification. In addition, the experimental data demonstrate a linear correlation between protein production rate and specific growth rate over a significant time period. This suggests a constant expression fraction within this window. For an Isopropyl β- d-1-thiogalactopyranoside (IPTG) biosensor, in five cellular contexts, expression fractions determined by the maximum method and the slope method produced strikingly similar dose–response parameters when independently fit to a Hill function. Furthermore, by analysing two more biosensors, for mercury and cumate detection, we demonstrate that the slope method can be applied effectively to various systems. Therefore, the concepts presented here provide convenient methods for obtaining dose–response parameters, clearly defining the time interval of their validity and offering a framework for interpreting typical biosensor outputs in terms of bacterial physiology. Graphical Abstract Nutrients, transformed by the action of the Nutrient Fixators (purple arrow), are used at a rate of ρ for Protein biosynthesis. The total rate ρ is multiplied by expression fractions fR, fC, fH, and fQ to obtain the biosynthesis rate (black arrows) of each proteome fraction ΦR, ΦC, ΦH, ΦQ, respectively. In a graph of Growth rate versus Proteome Fraction Production Rate, a linear function (green lines) can be observed, and its slope is equal to the expression fraction at each condition.

The Mycobacterium tuberculosis RNA polymerase (MtbRNAP) is the target of the first-line anti-tuberculosis inhibitor rifampin, however, the emergence of rifampin resistance necessitates the development of new antibiotics. Here, we communicate the first single-molecule characterization of MtbRNAP elongation and its inhibition by three diverse small-molecule inhibitors: N(α)-aroyl-N-aryl-phenylalaninamide (D-IX216), streptolydigin (Stl), and pseudouridimycin (PUM) using high-resolution optical tweezers. Compared to Escherichia coli RNA polymerase (EcoRNAP), MtbRNAP transcribes more slowly, has similar mechanical robustness, and only weakly recognizes E. coli pause sequences. The three small-molecule inhibitors of MtbRNAP exhibit strikingly different effects on transcription elongation. In the presence of D-IX216, which inhibits RNAP active-center bridge-helix motions required for nucleotide addition, the enzyme exhibits transitions between slowly and super-slowly elongating inhibited states. Stl, which inhibits the RNAP trigger-loop motions also required for nucleotide addition, inhibits RNAP primarily by inducing pausing and backtracking. PUM, a nucleoside analog of UTP, in addition to acting as a competitive inhibitor, induces the formation of slowly elongating RNAP inhibited states. Our results indicate that the three classes of small-molecule inhibitors affect the enzyme in distinct ways and show that the combination of Stl and D-IX216, which both target the RNAP bridge helix, has a strong synergistic effect on the enzyme.

Whole-cell biosensors could serve as eco-friendly and cost-effective alternatives for detecting potentially toxic bioavailable heavy metals in aquatic environments. However, they often fail to meet practical requirements due to an insufficient limit of detection (LOD) and high background noise. In this study, we designed a synthetic genetic circuit specifically tailored for detecting ionic mercury, which we applied to environmental samples collected from artisanal gold mining sites in Peru. We developed two distinct versions of the biosensor, each utilizing a different reporter protein: a fluorescent biosensor (Mer-RFP) and a colorimetric biosensor (Mer-Blue). Mer-RFP enabled real-time monitoring of the culture’s response to mercury samples using a plate reader, whereas Mer-Blue was analysed for colour accumulation at the endpoint using a specially designed, low-cost camera setup for harvested cell pellets. Both biosensors exhibited negligible baseline expression of their respective reporter proteins and responded specifically to HgBr₂ in pure water. Mer-RFP demonstrated a linear detection range from 1 nM to 1 μM, whereas Mer-Blue showed a linear range from 2 nM to 125 nM. Our biosensors successfully detected a high concentration of ionic mercury in the reaction bucket where artisanal miners produce a mercury–gold amalgam. However, they did not detect ionic mercury in the water from active mining ponds, indicating a concentration lower than 3.2 nM Hg²⁺—a result consistent with chemical analysis quantitation. Furthermore, we discuss the potential of Mer-Blue as a practical and affordable monitoring tool, highlighting its stability, reliance on simple visual colorimetry, and the possibility of sensitivity expansion to organic mercury.

Whole cell biosensors could serve as eco-friendly and cost-effective alternatives for detecting potentially toxic bioavailable heavy metals in aquatic environments. However, they often fail to meet practical requirements due to an insufficient limit of detection (LOD) and high background noise. In this study, we designed a synthetic genetic circuit specifically tailored for detecting ionic mercury, which we applied to environmental samples collected from artisanal gold mining sites in Peru. We developed two distinct versions of the biosensor, each utilizing a different reporter protein: a fluorescent biosensor (Mer-RFP) and a colorimetric biosensor (Mer-Blue). Mer-RFP enabled real-time monitoring of the culture’s response to mercury samples using a plate reader, whereas Mer-Blue was analysed for colour accumulation at the endpoint using a specially designed, low-cost camera set up for harvested cell pellets. Both biosensors exhibited negligible baseline expression of their respective reporter proteins and responded specifically to HgBr 2 in pure water. Mer-RFP demonstrated a linear detection range from 1 nM to 1 μM, whereas Mer-Blue showed a linear range from 2 nM to 125 nM. Our biosensors successfully detected a high concentration of ionic mercury in the reaction bucket where artisanal miners produce a mercury-gold amalgam. However, they did not detect ionic mercury in the water from active mining ponds, indicating a concentration lower than 3.2 nM Hg 2+ -a result consistent with chemical analysis quantitation. Furthermore, we discuss the potential of Mer-Blue as a practical and affordable monitoring tool, highlighting its stability, reliance on simple visual colorimetry, and the possibility of sensitivity expansion to organic mercury.

Many studies characterize transcription factors and other regulatory elements to control the expression of heterologous genes in recombinant systems. However, most lack a formal approach to analyse the parameters and context-specific variations of these regulatory components. This study addresses this gap by establishing formal and convenient methods for characterising regulatory circuits. We model the bacterial cell as a collection of a small number of proteome fractions. Then, we derive the proteome fraction over time and obtain a general theorem describing its change as a function of its expression fraction, which represents a specific portion of the total biosynthesis flux of the cell. Formal deduction reveals that when the proteome fraction reaches a maximum, it becomes equivalent to its expression fraction. This equation enables the reliable measurement of the expression fraction through direct protein quantification. In addition, experimental data demonstrate a linear correlation between protein production rate and specific growth rate over a significant time period. This suggests a constant expression fraction within this window. The expression fractions estimated from the slopes of these intervals and those obtained from maximum protein amount points can both be independently fitted to a Hill function. In the case of an IPTG biosensor, in five cellular contexts, expression fractions determined by the maximum method and the slope method produced similar dose-response parameters. Additionally, by analysing two more biosensors, for mercury and cumate detection, we demonstrate that the slope method can be effectively applied to various systems, generating reliable Hill function parameters.

The T7 expression system is commonly used to obtain high yields of heterologous proteins in Escherichia coli. Still, laboratories empirically optimize its use, frequently with little information for rationally choosing the change of settings in each case. Here, we monitored the expression of green fluorescent protein (GFP) as a function of growth in three strains, with and without additional LacI repressor and IPTG added at different times. BL21(DE3) strain showed the best yield; however, its inability to repress T7 harmed the culture unless additional LacI was provided. The BLR(DE3) and MG1655 strains suppressed T7 leaking by themselves but differed in the outcomes of additional LacI. While LacI overexpression improved BLR’s growth and yield, it severely harmed the MG1655 culture. In all cases, early induction with IPTG offered a better outcome than adding it too late. MG1655 was least sensitive to this timing thanks to its capability of keeping a high growth rate for longer. Notably, the GFP production rate was linear to growth rates throughout the culture, meaning that the ribosomal fraction allocated to GFP production was constant at all the analyzed time points. This observation is consistent with a general, time-resolved regulation function and supports the interpretation of our data through a proteome allocation model (PAM). A simple PAM simulated correctly the carbon overflow triggered by heterologous overexpression, indicating that if any anabolic fraction is added to compete for proteome allocation, the rate of precursors consumption will decrease, thus leading to said overflow. This model proposes that a LacI promiscuous repression activity can explain its observed opposite effects on BLR(DE3) and MG1655 strains. Through different levels of downregulation, the carbon fixating proteome fraction would reach a state closer or farther from optimum in each host.