How to Lengthen the Long-Term Stability of Enzyme Membranes: Trends and Strategies

AbMelt: Learning antibody thermostability from molecular dynamics

Antibody thermostability is challenging to predict from sequence and/or structure. This difficulty is likely due to the absence of direct entropic information. Herein, we present AbMelt where we model the inherent flexibility of homologous antibody structures using molecular dynamics simulations at three temperatures and learn the relevant descriptors to predict the temperatures of aggregation (Tagg), melt onset (Tm,on), and melt (Tm). We observed that the radius of gyration deviation of the complementarity determining regions at 400 K is the highest Pearson correlated descriptor with aggregation temperature (rp = -0.68 ± 0.23) and the deviation of internal molecular contacts at 350 K is the highest correlated descriptor with both Tm,on (rp = -0.74 ± 0.04) as well as Tm (rp = -0.69 ± 0.03). Moreover, after descriptor selection and machine learning regression, we predict on a held-out test set containing both internal and public data and achieve robust performance for all endpoints compared with baseline models (Tagg R2 = 0.57 ± 0.11, Tm,on R2 = 0.56 ± 0.01, and Tm R2 = 0.60 ± 0.06). In addition, the robustness of the AbMelt molecular dynamics methodology is demonstrated by only training on <5% of the data and outperforming more traditional machine learning models trained on the entire data set of more than 500 internal antibodies. Users can predict thermostability measurements for antibody variable fragments by collecting descriptors and using AbMelt, which has been made available.

Low-Cost Biosensor Technologies for Rapid Detection of COVID-19 and Future Pandemics

Many systems have been designed for the detection of SARS-CoV-2, which is the virus that causes COVID-19. SARS-CoV-2 is readily transmitted, resulting in the rapid spread of disease in human populations. Frequent testing at the point of care (POC) is a key aspect for controlling outbreaks caused by SARS-CoV-2 and other emerging pathogens, as the early identification of infected individuals can then be followed by appropriate measures of isolation or treatment, maximizing the chances of recovery and preventing infectious spread. Diagnostic tools used for high-frequency testing should be inexpensive, provide a rapid diagnostic response without sophisticated equipment, and be amenable to manufacturing on a large scale. The application of these devices should enable large-scale data collection, help control viral transmission, and prevent disease propagation. Here we review functional nanomaterial-based optical and electrochemical biosensors for accessible POC testing for COVID-19. These biosensors incorporate nanomaterials coupled with paper-based analytical devices and other inexpensive substrates, traditional lateral flow technology (antigen and antibody immunoassays), and innovative biosensing methods. We critically discuss the advantages and disadvantages of nanobiosensor-based approaches compared to widely used technologies such as PCR, ELISA, and LAMP. Moreover, we delineate the main technological, (bio)chemical, translational, and regulatory challenges associated with developing functional and reliable biosensors, which have prevented their translation into the clinic. Finally, we highlight how nanobiosensors, given their unique advantages over existing diagnostic tests, may help in future pandemics.

Enzymatic biofuel cells based on protective hydrophobic carbon paste electrodes: towards epidermal bioenergy harvesting in the acidic sweat environment

The operation of wearable epidermal biofuel cells is prone to rapid irreversible deactivation effects under dynamic sweat pH changes from neutral to acidic. We demonstrate that the encapsulation of lactate-oxidase (LOx) within a hydrophobic protective carbon-paste anode imparts unusually high stability during dynamically changing pH fluctuations and allows the BFC to continue harvesting the lactate bioenergy even after long exposures to acidic conditions. The unique power-recovery ability of the carbon-paste BFC after its failure in harsh pH is attributed to the protective action of the non-polar paste environment.

Immobilization of Enzymes on a Phospholipid Bionically Modified Polysulfone Gradient-Pore Membrane for the Enhanced Performance of Enzymatic Membrane Bioreactors

Enzymatic membrane bioreactors (EMBRs), with synergistic catalysis-separation performance, have increasingly been used for practical applications. Generally, the membrane properties, particularly the pore structures and interface interactions, have a significant impact on the catalytic efficiency of the EMBR. Therefore, a biomimetic interface based on a phospholipid assembled onto a polysulfone hollow-fiber membrane with perfect radial gradient pores (RGM-PSF) has been prepared in this work to construct a highly efficient and stable EMBR. On account of the special pore structure of the RGM-PSF with the apertures decreasing gradually from the inner side to the outer side, the enzyme molecules could be evenly distributed on the three-dimensional skeleton of the membrane. In addition, the supported phospholipid layer in the membrane, prepared by physical adsorption, was used for the immobilization of the enzymes, which provides sufficient linkage to prevent the enzymes from leaching but also accommodates as many enzyme molecules as possible to retain high bioactivity. The properties of the EMBR were studied by using lipase from Candida rugosa for the hydrolysis of glycerol triacetate as a model. Energy-dispersive X-ray and circular dichroism spectroscopy were employed to observe the effect of lecithin on the membrane and structure changes in the enzyme, respectively. The operational conditions were investigated to optimize the performance of the EMBR by testing substrate concentrations from 0.05 to 0.25 M, membrane fluxes from 25.5 to 350.0 L·m-2·h-1, and temperatures from 15 to 55 °C. As a result, the obtained EMBR showed a desirable performance with 42% improved enzymatic activity and 78% improved catalytic efficiency relative to the unmodified membrane.

A Biosensor-CMOS Platform and Integrated Readout Circuit in 0.18-μm CMOS Technology for Cancer Biomarker Detection

This paper presents a biosensor-CMOS platform for measuring the capacitive coupling of biorecognition elements. The biosensor is designed, fabricated, and tested for the detection and quantification of a protein that reveals the presence of early-stage cancer. For the first time, the spermidine/spermine N1 acetyltransferase (SSAT) enzyme has been screened and quantified on the surface of a capacitive sensor. The sensor surface is treated to immobilize antibodies, and the baseline capacitance of the biosensor is reduced by connecting an array of capacitors in series for fixed exposure area to the analyte. A large sensing area with small baseline capacitance is implemented to achieve a high sensitivity to SSAT enzyme concentrations. The sensed capacitance value is digitized by using a 12-bit highly digital successive-approximation capacitance-to-digital converter that is implemented in a 0.18 μm CMOS technology. The readout circuit operates in the near-subthreshold regime and provides power and area efficient operation. The capacitance range is 16.137 pF with a 4.5 fF absolute resolution, which adequately covers the concentrations of 10 mg/L, 5 mg/L, 2.5 mg/L, and 1.25 mg/L of the SSAT enzyme. The concentrations were selected as a pilot study, and the platform was shown to demonstrate high sensitivity for SSAT enzymes on the surface of the capacitive sensor. The tested prototype demonstrated 42.5 μS of measurement time and a total power consumption of 2.1 μW.