mebipred: identifying metal binding potential in protein sequence

Motivation

metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability.

Results

we developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is over 80% accurate in recognizing proteins that bind metal ion-containing ligands; the specific identity of 11 ubiquitously present metal ions can also be annotated. mebipred is reference-free, i.e. no sequence alignments are involved, and is thus faster than alignment-based methods; it is also more accurate than other sequence-based prediction methods. Additionally, mebipred can identify protein metal-binding capabilities from short sequence stretches, e.g. translated sequencing reads, and, thus, may be useful for the annotation of metal requirements of metagenomic samples. We performed an analysis of available microbiome data and found that ocean, hot spring sediments and soil microbiomes use a more diverse set of metals than human host-related ones. For human microbiomes, physiological conditions explain the observed metal preferences. Similarly, subtle changes in ocean sample ion concentration affect the abundance of relevant metal-binding proteins. These results highlight mebipred’s utility in analyzing microbiome metal requirements.

Availability and implementation

mebipred is available as a web server at services.bromberglab.org/mebipred and as a standalone package at https://pypi.org/project/mymetal/.

Supplementary information

Supplementary data are available at Bioinformatics online.

A virucidal face mask based on the reverse-flow reactor concept for thermal inactivation of SARS-CoV-2

While facial coverings reduce the spread of SARS-CoV-2 by viral filtration, masks capable of viral inactivation by heating can provide a complementary method to limit transmission. Inspired by reverse-flow chemical reactors, we introduce a new virucidal face mask concept driven by the oscillatory flow of human breath. The governing heat and mass transport equations are solved to evaluate virus and CO₂ transport. Given limits imposed by the kinetics of SARS-CoV-2 thermal inactivation, human breath, safety, and comfort, heated masks may inactivate SARS-CoV-2 to medical-grade sterility. We detail one design, with a volume of 300 ml at 90°C that achieves a 3-log reduction in viral load with minimal impedance within the mask mesh, with partition coefficient around 2. This is the first quantitative analysis of virucidal thermal inactivation within a protective face mask, and addresses a pressing need for new approaches for personal protective equipment during a global pandemic.

Noble-gas-infused neoprene closed-cell foams achieving ultra-low thermal conductivity fabrics

Herein, we develop, demonstrate, and model a repeatable process for synthesizing ultra-low-thermal-conductivity closed-cell neoprene garments by infusing high-molecular-weight noble gases.

Effect of Surface Oxidation on the Onset of Nucleate Boiling in a Materials Test Reactor Coolant Channel

The onset of nucleate boiling (ONB) serves as the thermal-hydraulic operating limit for many research and test reactors. However, boiling incipience under forced convection has not been well-characterized in narrow channel geometries or for oxidized surface conditions. This study presents experimental data for the ONB in vertical upflow of deionized (DI) water in a simulated materials test reactor (MTR) coolant channel. The channel gap thickness and aspect ratio were 1.96 mm and 29∶1, respectively. Boiling surface conditions were carefully controlled and characterized, with both heavily oxidized and native oxide surfaces tested. Measurements were performed for mass fluxes ranging from 750 to 3000  kg/m2 s and for subcoolings ranging from 10 to 45°C. ONB was identified using a combination of high-speed visual observation, surface temperature measurements, and channel pressure drop measurements. Surface temperature measurements were found to be most reliable in identifying the ONB. For the nominal (native oxide) surface, results indicate that the correlation of Bergles and Rohsenow, when paired with the appropriate single-phase heat transfer correlation, adequately predicts the ONB heat flux. Incipience on the oxidized surface occurred at a higher heat flux and superheat than on the plain surface.

Infrared thermometry study of nanofluid pool boiling phenomena

Infrared thermometry was used to obtain first-of-a-kind, time- and space-resolved data for pool boiling phenomena in water-based nanofluids with diamond and silica nanoparticles at low concentration (<0.1 vol.%). In addition to macroscopic parameters like the average heat transfer coefficient and critical heat flux [CHF] value, more fundamental parameters such as the bubble departure diameter and frequency, growth and wait times, and nucleation site density [NSD] were directly measured for a thin, resistively heated, indium-tin-oxide surface deposited onto a sapphire substrate. Consistent with other nanofluid studies, the nanoparticles caused deterioration in the nucleate boiling heat transfer (by as much as 50%) and an increase in the CHF (by as much as 100%). The bubble departure frequency and NSD were found to be lower in nanofluids compared with water for the same wall superheat. Furthermore, it was found that a porous layer of nanoparticles built up on the heater surface during nucleate boiling, which improved surface wettability compared with the water-boiled surfaces. Using the prevalent nucleate boiling models, it was possible to correlate this improved surface wettability to the experimentally observed reductions in the bubble departure frequency, NSD, and ultimately to the deterioration in the nucleate boiling heat transfer and the CHF enhancement.

Speciation of polonium released from molten lead bismuth

The alpha-emitter 210Po is an activation product of liquid lead-bismuth, a low melting eutectic under investigation as a coolant of the next generation fast nuclear reactors. Experiments were performed to measure the gaseous polonium chemical species for assessing the radioactivity release from a Pb-Bi bath upon contact with a gas stream. The vapor pressure of lead polonide was measured over the 400-550°C temperature range and found to be in agreement with an existing correlation derived from data at higher temperatures. Also, it was experimentally confirmed that the presence of steam in the gas stream above the Pb-Bi melt substantially increases the amount of polonium released due to the formation of the volatile compound H2Po. The free-energy variation of the H2Po formation reaction was determined, permitting the calculation of the Po gas phase speciation under the experimental conditions.

Mean-field versus microconvection effects in nanofluid thermal conduction

Transient hot-wire data on thermal conductivity of suspensions of silica and perfluorinated particles show agreement with the mean-field theory of Maxwell but not with the recently postulated microconvection mechanism. The influence of interfacial thermal resistance, convective effects at microscales, and the possibility of thermal conductivity enhancements beyond the Maxwell limit are discussed.