Post-transcriptional control of mitochondrial gene expression, including the processing and generation of mature transcripts as well as their degradation, is a key regulatory step in gene expression in human mitochondria. Consequently, identification of the proteins responsible for RNA processing and degradation in this organelle is of great importance. The metallo-β-lactamase (MBL) is a candidate protein family that includes ribo- and deoxyribonucleases. In this study, we discovered a function for LACTB2, an orphan MBL protein found in mammalian mitochondria. Solving its crystal structure revealed almost perfect alignment of the MBL domain with CPSF73, as well as to other ribonucleases of the MBL superfamily. Recombinant human LACTB2 displayed robust endoribonuclease activity on ssRNA with a preference for cleavage after purine-pyrimidine sequences. Mutational analysis identified an extended RNA-binding site. Knockdown of LACTB2 in cultured cells caused a moderate but significant accumulation of many mitochondrial transcripts, and its overexpression led to the opposite effect. Furthermore, manipulation of LACTB2 expression resulted in cellular morphological deformation and cell death. Together, this study discovered that LACTB2 is an endoribonuclease that is involved in the turnover of mitochondrial RNA, and is essential for mitochondrial function in human cells.
Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.
Bioluminescence is visible light produced and emitted by living cells using various biological systems (e.g. luxCDABE cassette). Today, this phenomenon is widely exploited in biological research, biotechnology and medical applications as a quantitative technique for the detection of biological signals. However, this technique has mostly been used to detect a single input only. In this work, we re-engineered the complex genetic structure of luxCDABE cassette to build a biological unit that can detect multi-inputs, process the cellular information and report the computation results. We first split the luxCDABE operon into several parts to create a genetic circuit that can compute a soft minimum in living cells. Then, we used the new design to implement an AND logic function with better performance as compared to AND logic functions based on protein-protein interactions. Furthermore, by controlling the reverse reaction of the luxCDABE cassette independently from the forward reaction, we built a comparator with a programmable detection threshold. Finally, we applied the redesigned cassette to build an incoherent feedforward loop that reduced the unwanted crosstalk between stress-responsive promoters (recA, katG). This work demonstrates the construction of genetic circuits that combine regulations of gene expression with metabolic pathways, for sensing and computing in living cells.
The early detection of blood in urine (hematuria) can play a crucial role in the treatment of serious diseases (e.g., infections, kidney disease, schistosomiasis, and cancer). Therefore, the development of low-cost portable biosensors for blood detection in urine has become necessary. Here, we designed an ultrasensitive whole-cell bacterial biosensor interfaced with an optoelectronic measurement module for heme detection in urine. Heme is a red blood cells (RBCs) component that is liberated from lysed cells. The bacterial biosensor includes Escherichia coli cells carrying a heme-sensitive synthetic promoter integrated with a luciferase reporter (luxCDABE) from Photorhabdus luminescens. To improve the bacterial biosensor performance, we re-engineered the genetic structure of luxCDABE operon by splitting it into two parts (luxCDE and luxAB). The luxCDE genes were regulated by the heme-sensitive promoter, and the luxAB genes were regulated by either constitutive or inducible promoters. We examined the genetic circuit's performance in synthetic urine diluent supplied with heme and in human urine supplied with lysed blood. Finally, we interfaced the bacterial biosensor with a light detection setup based on a commercial optical measurement single-photon avalanche photodiode (SPAD). The whole-cell biosensor was tested in human urine with lysed blood, demonstrating a low-cost, portable, and easy-to-use hematuria detection with an ON-to-OFF ratio of 6.5-fold for blood levels from 5 × 10 4 to 5 × 10 5 RBC per mL of human urine.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.