High-throughput Screening Approach Research Articles

A novel high-throughput screening method for identifying compounds that inhibit plasmid conjugation

Plasmid conjugation is an important contributing factor to the spread of antibiotic resistance among bacteria, posing a significant global health threat. Our method introduces an innovative high-throughput screening approach to identify compounds that inhibit or reduce conjugation, addressing the need for new strategies against the spread of antimicrobial resistance.Using Escherichia coli strains as donor and recipient, we screened 3500 compounds from a library provided by ABAC Therapeutics. Each 96 –well plate was loaded with 88 different compounds and bacterial cultures. Every plate also included negative and positive controls of conjugation. After an hour, cultures from wells were spotted on agar plates and assessed visually. Compounds that showed a visible effect on conjugation were retested. Six compounds targeting conjugation were found, showing promise for further analysis.

ZN-2: A natural product small molecule stabilizes p53Y220C to restore p53 mutation – A high-throughput virtual screening approach

ZN-2: A natural product small molecule stabilizes p53Y220C to restore p53 mutation – A high-throughput virtual screening approach

A robust high-throughput functional screening assay for plant pathogen effectors using the TMV-GFP vector.

Uncovering the function of phytopathogen effectors is crucial for understanding mechanisms of pathogen pathogenicity and for improving our ability to protect plants from diseases. An increasing number of effectors have been predicted in various plant pathogens. Functional characterization of these effectors has become a major focus in the study of plant-pathogen interactions. In this study, we designed a novel screening system that combines the TMV (tobacco mosaic virus)-GFP vector and Agrobacterium-mediated transient expression in the model plant Nicotiana benthamiana. This system enables the rapid identification of effectors that interfere with plant immunity. The biological function of these effectors can be easily evaluated by observing the GFP fluorescence signal using a UV lamp within just a few days. To evaluate the TMV-GFP system, we initially tested it with well-described virulence and avirulence type III effectors from the bacterial pathogen Ralstonia solanacearum. After proving the accuracy and efficiency of the TMV-GFP system, we successfully screened a novel virulence effector, RipS1, using this approach. Furthermore, using the TMV-GFP system, we reproduced consistent results with previously known cytoplasmic effectors from a diverse array of pathogens. Additionally, we demonstrated the effectiveness of the TMV-GFP system in identifying apoplastic effectors. The easy operation, time-saving nature, broad effectiveness, and low technical requirements of the TMV-GFP system make it a promising approach for high-throughput screening of effectors with immune interference activity from various pathogens.

High-resolution melt curve analysis: An approach for variant detection in the TPO gene of congenital hypothyroid patients in Bangladesh.

TPO (Thyroid Peroxidase) is known to be one of the major genes involved in congenital hypothyroid patients with thyroid dyshormonogenesis. The present study aims to validate high-resolution melting (HRM) curve analysis as a substitute method for Sanger sequencing, focusing on the frequently observed non-synonymous mutations c.1117G>T, c.1193G>C, and c.2173A>C in the TPO gene in patients from Bangladesh. We enrolled 36 confirmed cases of congenital hypothyroid patients with dyshormonogenesis to establish the HRM method. Blood specimens were collected, and DNA was extracted followed by PCR and Sanger sequencing. Among the 36 specimens, 20 were pre-sequenced, and variants were characterized through Sanger sequencing. Following pre-sequencing, the 20 pre-sequenced specimens underwent real-time PCR-HRM curve analysis to determine the proper HRM condition for separating the three variations from the wild-type state into heterozygous and homozygous states. Furthermore, 16 unknown specimens were subjected to HRM analysis to validate the method. This method demonstrated a sensitivity and specificity of 100 percent in accurately discerning wild-type alleles from both homozygous and heterozygous states of c.1117G>T (23/36; 63.8%), c.1193G>C (30/36; 83.3%), and c.2173A>C (23/36; 63.8%) variants frequently encountered among 36 Bangladeshi patients. The HRM data was found to be similar to the sequencing result, thus confirming the validity of the HRM approach for TPO gene variant detection. In conclusion, HRM-based molecular technique targeting variants c.1117G>T, c.1193G>C, and c.2173A>C could be used as a high throughput, rapid, reliable, and cost-effective screening approach for the detection of all common mutations in TPO gene in Bangladeshi patients with dyshormonogenesis.

Abstract LB030: Building a platform of validated high throughput screening approaches for molecular glue degrader identification

Abstract Over recent years, Induced proximity therapeutics (IPT) and targeted protein degradation (TPD) approaches have become increasingly popular. Whilst significant initial efforts focused upon heterobifunctional degraders, molecular glue degraders (MGDs) represent the next generation proximity-based drugs, but their rational discovery remains challenging. Here, we describe unbiased and broadly applicable approaches for molecular glue hit ID through the development of a suite of orthogonal and highly complementary screening approaches, relying on Homogeneous Time-Resolved Fluorescence (HTRF), Surface Plasmon Resonance (SPR) and High Content Imaging (HCI). To demonstrate the utility of these assays, we have focussed on the therapeutically relevant protein SOS1 as a model target. SOS1 is the major guanine nucleotide exchange factor (GEF) for KRAS, where inhibition of the SOS1/KRAS interaction reduces tumor growth in preclinical settings, and small molecule inhibitors of the SOS1/KRAS interaction are currently undergoing clinical testing for KRAS driven cancers. Our HTRF approach measures the induced interaction between the ubiquitin ligase CRBN/DDB1 and the SOS1 protein. The assay was successfully developed and validated in a miniaturized format utilizing a bifunctional tool compound as a positive control. Complementing our HTRF based approach, we also developed a highly sensitive SPR assay for detecting compounds that generate a ternary complex with CRBN/DDB1. These assay formats are amenable for large scale HTS screening, and as proof-of-concept we have established workflows and screened compound collections from the Sygnature LeadFinder and fragment libraries, in each of these assay platforms. Our combined biochemical/biophysical approach to glue identification using HTRF and SPR demonstrates the successful and scalable use of these methodologies for HTS, with the exciting potential for identification of novel MGD candidates for SOS1. To further complement these strategies for glue identification, we have additionally developed a functional cell-based approach utilizing HCI. HCI offers a medium-high throughput approach to monitor endogenous protein abundance and localization in complex cellular models. One major advantage of imaging assays is that they are amenable to multiplexing, allowing simultaneous detection of target engagement, biomarker analysis and compound toxicity. Here, we showcase HCI as a robust, high throughput method of screening for induced protein degradation at the endogenous level, again focusing on the KRAS pathway. Using this approach we quantified endogenous protein abundance in response to compound treatment, as well as downstream effects in the RAS pathway. Together, these approaches demonstrate multiple, complementary options for identifying molecular glue degraders. Further, the described assays are also applicable for screening and characterization of bifunctional degrader compounds. This platform is poised to identify high quality lead compounds across a range of oncology targets in areas of unmet clinical need. Citation Format: Allan Jordan, Philip Addis, Toby Allen, Tarun Ayra, Sarah Beck, Roslyn Brant, Roland Hjerpe, Benoit Gourdet, Martin Jennings, Rachel Lawrence, Sigrun Campbell-Maurer, Pei Cing Ng, Lyn Parkinson, Eva Rejnowicz, Gonzalo Robles, Elizabeth Rosethorne, Joshua Shaw, Duncan Smith, Denise Swift, Daniel Tait, Stuart Thomson, Chris Tomlinson, Ailsa Townley, Stephanie Ward, Clare Wilson. Building a platform of validated high throughput screening approaches for molecular glue degrader identification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB030.

RapidAIM 2.0: a high-throughput assay to study functional response of human gut microbiome to xenobiotics.

Aim: Our gut microbiome has its own functionalities which can be modulated by various xenobiotic and biotic components. The development and application of a high-throughput functional screening approach of individual gut microbiomes accelerates drug discovery and our understanding of microbiome-drug interactions. We previously developed the rapid assay of individual microbiome (RapidAIM), which combined an optimized culturing model with metaproteomics to study gut microbiome responses to xenobiotics. In this study, we aim to incorporate automation and multiplexing techniques into RapidAIM to develop a high-throughput protocol. Methods: To develop a 2.0 version of RapidAIM, we automated the protein analysis protocol, and introduced a tandem mass tag (TMT) multiplexing technique. To demonstrate the typical outcome of the protocol, we used RapidAIM 2.0 to evaluate the effect of prebiotic kestose on ex vivo individual human gut microbiomes biobanked with five different workflows. Results: We describe the protocol of RapidAIM 2.0 with extensive details on stool sample collection, biobanking, in vitro culturing and stimulation, sample processing, metaproteomics measurement, and data analysis. The analysis depth of 5,014 ± 142 protein groups per multiplexed sample was achieved. A test on five biobanking methods using RapidAIM 2.0 showed the minimal effect of sample processing on live microbiota functional responses to kestose. Conclusions: Depth and reproducibility of RapidAIM 2.0 are comparable to previous manual label-free metaproteomic analyses. In the meantime, the protocol realizes culturing and sample preparation of 320 samples in six days, opening the door to extensively understanding the effects of xenobiotic and biotic factors on our internal ecology.

Spinocerebellar Ataxia Type 3 Pathophysiology-Implications for Translational Research and Clinical Studies.

The spinocerebellar ataxias (SCA) comprise a group of inherited neurodegenerative diseases. Machado-Joseph Disease (MJD) or spinocerebellar ataxia 3 (SCA3) is the most common autosomal dominant form, caused by the expansion of CAG repeats within the ataxin-3 (ATXN3) gene. This mutation results in the expression of an abnormal protein containing long polyglutamine (polyQ) stretches that confers a toxic gain of function and leads to misfolding and aggregation of ATXN3 in neurons. As a result of the neurodegenerative process, SCA3 patients are severely disabled and die prematurely. Several screening approaches, e.g., druggable genome-wide and drug library screenings have been performed, focussing on the reduction in stably overexpressed ATXN3(polyQ) protein and improvement in the resultant toxicity. Transgenic overexpression models of toxic ATXN3, however, missed potential modulators of endogenous ATXN3 regulation. In another approach to identify modifiers of endogenous ATXN3 expression using a CRISPR/Cas9-modified SK-N-SH wild-type cell line with a GFP-T2A-luciferase (LUC) cassette under the control of the endogenous ATXN3 promotor, four statins were identified as potential activators of expression. We here provide an overview of the high throughput screening approaches yet performed to find compounds or genomic modifiers of ATXN3(polyQ) toxicity in different SCA3 model organisms and cell lines to ameliorate and halt SCA3 progression in patients. Furthermore, the putative role of cholesterol in neurodegenerative diseases (NDDs) in general and SCA3 in particular is discussed.

High-throughput mutagenesis and screening approach for the identification of drug-resistant mutations in the rifampicin resistance-determining region of mycobacteria

Rifampicin is the most powerful first-line antibiotic for tuberculosis, which is caused by Mycobacterium tuberculosis. Although accumulating evidence from sequencing data of clinical M. tuberculosis isolates suggested that mutations in the rifampicin-resistance-determining region (RRDR) are strongly associated with rifampicin resistance, the comprehensive characterisation of RRDR polymorphisms that confer this resistance remains challenging. By incorporating I-SceI sites for I-SceI-based integrant removal and utilizing an L5 swap strategy, we efficiently replaced the integrated plasmid with alternative alleles, making mass allelic exchange feasible in mycobacteria. Using this method to establish a fitness-related gain-of function screen, we generated a mutant library that included all single-amino-acid mutations in the RRDR, and identified the important positions corresponding to some well-known rifampicin-resistance mutations (Q513, D516, S522, H525, R529, S531). We also detected a novel two-point mutation located in the RRDR confers a fitness advantage to M. smegmatis in the presence or absence of rifampicin. Our method provides a comprehensive insight into the growth phenotypes of RRDR mutants and should facilitate the development of anti-tuberculosis drugs.

Abstract 6988: TP53RK regulates DNA replication by CDC7-mediated MCM helicase phosphorylation in colorectal cancer

Abstract Background: We identify TP53 regulating kinase (TP53RK), which showed the highest cell growth inhibition efficiency in six colon cancer cell lines. TP53RK is overexpressed in various cancer types, including multiple myeloma and skin cancer, but the mechanism for its tumorigenesis in colon cancer is unknown. Therefore, this study aims to reveal the tumorigenesis mechanism of TP53RK, which is overexpressed in Colorectal Cancer (CRC), through global and phospho-proteomics. Method: A total 5 CRC cell lines (HT29, SW480, HCT116, H508 and CaCO2), colon normal fibroblast CRL1459, HCT116 p53 null cell and patient-derived normal organoid were used. Immunoblotting, MTT assay, Colony formation assay, Annexin-V assay and cell cycle analysis were performed for evaluation of TP53RK loss-of-function. With kinase-substrate enrichment analysis with phospho-proteome analysis, MCM2 was found to be a substrate for the kinase regulated by TP53RK. Results: High-throughput genetic screening approach have been widely applied to the study the gene function and molecular mechanism associated with tumorigenesis. By using genome-wide CRISPR/Cas9 library screening, we identify TP53RK, the first committed negative-selected gene, as a tyrosine kinase in the colorectal cancer(CRC) specific biomarker. Through proteome analysis, we found that depletion of TP53RK can hypo-phosphorylate the DNA helicase complex, MCM2 (minichromosome maintenance protein2). According to previous studies, the phosphorylation of MCM2 is regulated by CDC7 (cell division cycle7), and the abnormal states of CDC7 and MCM2 cause DNA replication disorder. Our results show that TP53RK expression is upregulated in CRC and its depletion results in decreased CDC7 expression and hypo-phosphorylation of the MCM complex. Decreased CDC7 expression due to its instability after TP53RK depletion can lead to DNA replication errors. DNA replication errors can lead cancer cells to apoptosis, suggesting that they may be a strategy for cancer treatment. In summary, we provide TP53RK as a novel prognostic and therapeutic target in CRC. Conclusion: To recapitulate briefly, our findings suggest that the interaction of TP53RK with CDC7 can regulate CDC7 protein stability and stabilized CDC7 can phosphorylate MCM2 to initiate DNA replication. In other words, because overexpression of TP53RK acts as an oncogene that promotes tumor progression in CRC, depletion of TP53RK can degrade CDC7 and induce colon cancer cells to death or regression. Citation Format: Younghee Choi, Ji-won Park, Jun-kyu Kang, Eun-ju Kim, Sang-Hyun Song, Eugene C. Yi, Tae-You Kim. TP53RK regulates DNA replication by CDC7-mediated MCM helicase phosphorylation in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6988.

Abstract 2904: Small molecule inhibitor targeting DDR represents a novel therapeutic strategy for the treatment of pancreatic ductal adenocarcinoma (PDAC)

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is ranked as the second leading cause of cancer-related mortality with a 5-year survival rate of merely 12%. The complexity of PDAC lies in its intrinsic resistance to treatment, attributable to the desmoplastic tumor microenvironment, characterized by an abundance of tumor-promoting extracellular matrix (ECM) and stromal cells. We hypothesize that Discoidin Domain Receptors (DDR), members of the receptor tyrosine kinase family known for their affinity to fibrillar collagens within the ECM, play an important role in promoting PDAC growth and progression. While several drugs targeting DDR proteins have been developed, no inhibitors to DDR proteins are specific or approved for PDAC treatment, thus necessitating the development of novel therapeutic interventions. Methods. A comprehensive high-throughput screening approach employing small molecule inhibitors was executed to identify authentic inhibitors targeting DDR. Subsequently, a rigorous evaluation of specificity of these small molecules was conducted through structural activity relationship (SAR) analyses and reference-based assessments. The efficacy of candidate inhibitors was assessed through functional assays, while mechanistic insights were gleaned using a multifaceted approach, including RNA-seq, real-time PCR, western blot analysis, in vivo experimentation, and Phospho-Receptor Tyrosine Kinase (RTK) profiling to discern any unintended off-target effects. Results: Using an unbiased screening approach, we identified 13 inhibitors that specifically target DDR. SAR studies and cellular thermal shift assay validated CIDD-0108633 (8633) as a bona fide DDR2 inhibitor. Functional assays and RNA-seq analyses demonstrated 8633's capacity to inhibit PDAC growth, metastatic potential, and expression of DNA replication, cell-cycle, and DNA damage repair genes. Combination therapy of 8633 with gemcitabine synergistically reduced PDAC cell viability and metastatic potential. Mechanistic studies revealed the role of ABC transporters in mediating gemcitabine resistance. RTK profiling shows moderate kinase selectivity. In vivo studies affirmed its antitumor effects. Conclusions: The results indicate that the selective inhibition of DDR with small molecule inhibitors suppresses PDAC cell growth and progression, implying that DDR inhibitors have the potential to be developed as safe and efficacious therapeutics for the treatment of pancreatic cancers. Citation Format: Trong Phat Do, Jack Prochnau, Prabhakar Pitta Venkata, Sajid Khan, Santosh Timilsina, Deepika Singh, Daisy Medina, Radhika Amaradhi, Daohong Zhou, Matthew Hart, Stanton McHardy, Manjeet Rao. Small molecule inhibitor targeting DDR represents a novel therapeutic strategy for the treatment of pancreatic ductal adenocarcinoma (PDAC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2904.

In vitro inflammation and toxicity assessment of pre- and post-incinerated organomodified nanoclays to macrophages using high-throughput screening approaches

BackgroundOrganomodified nanoclays (ONC), two-dimensional montmorillonite with organic coatings, are increasingly used to improve nanocomposite properties. However, little is known about pulmonary health risks along the nanoclay life cycle even with increased evidence of airborne particulate exposures in occupational environments. Recently, oropharyngeal aspiration exposure to pre- and post-incinerated ONC in mice caused low grade, persistent lung inflammation with a pro-fibrotic signaling response with unknown mode(s) of action. We hypothesized that the organic coating presence and incineration status of nanoclays determine the inflammatory cytokine secretary profile and cytotoxic response of macrophages. To test this hypothesis differentiated human macrophages (THP-1) were acutely exposed (0–20 µg/cm2) to pristine, uncoated nanoclay (CloisNa), an ONC (Clois30B), their incinerated byproducts (I-CloisNa and I-Clois30B), and crystalline silica (CS) followed by cytotoxicity and inflammatory endpoints. Macrophages were co-exposed to lipopolysaccharide (LPS) or LPS-free medium to assess the role of priming the NF-κB pathway in macrophage response to nanoclay treatment. Data were compared to inflammatory responses in male C57Bl/6J mice following 30 and 300 µg/mouse aspiration exposure to the same particles.ResultsIn LPS-free media, CloisNa exposure caused mitochondrial depolarization while Clois30B exposure caused reduced macrophage viability, greater cytotoxicity, and significant damage-associated molecular patterns (IL-1α and ATP) release compared to CloisNa and unexposed controls. LPS priming with low CloisNa doses caused elevated cathepsin B/Caspage-1/IL-1β release while higher doses resulted in apoptosis. Clois30B exposure caused dose-dependent THP-1 cell pyroptosis evidenced by Cathepsin B and IL-1β release and Gasdermin D cleavage. Incineration ablated the cytotoxic and inflammatory effects of Clois30B while I-CloisNa still retained some mild inflammatory potential. Comparative analyses suggested that in vitro macrophage cell viability, inflammasome endpoints, and pro-inflammatory cytokine profiles significantly correlated to mouse bronchioalveolar lavage inflammation metrics including inflammatory cell recruitment.ConclusionsPresence of organic coating and incineration status influenced inflammatory and cytotoxic responses following exposure to human macrophages. Clois30B, with a quaternary ammonium tallow coating, induced a robust cell membrane damage and pyroptosis effect which was eliminated after incineration. Conversely, incinerated nanoclay exposure primarily caused elevated inflammatory cytokine release from THP-1 cells. Collectively, pre-incinerated nanoclay displayed interaction with macrophage membrane components (molecular initiating event), increased pro-inflammatory mediators, and increased inflammatory cell recruitment (two key events) in the lung fibrosis adverse outcome pathway.

Type 1 fimbriae-mediated collective protection against type 6 secretion system attacks.

Bacterial competition may rely on secretion systems such as the type 6 secretion system (T6SS), which punctures and releases toxic molecules into neighboring cells. To subsist, bacterial targets must counteract the threats posed by T6SS-positive competitors. In this study, we used a comprehensive genome-wide high-throughput screening approach to investigate the dynamics of interbacterial competition. Our primary goal was to identify deletion mutants within the well-characterized E. coli K-12 single-gene deletion library, the Keio collection, that demonstrated resistance to T6SS-mediated killing by the enteropathogenic bacterium Cronobacter malonaticus. We identified 49 potential mutants conferring resistance to T6SS and focused our interest on a deletion mutant (∆fimE) exhibiting enhanced expression of type 1 fimbriae. We demonstrated that the presence of type 1 fimbriae leads to the formation of microcolonies and thus protects against T6SS-mediated assaults. Collectively, our study demonstrated that adhesive structures such as type 1 fimbriae confer collective protective behavior against T6SS attacks.IMPORTANCEType 6 secretion systems (T6SS) are molecular weapons employed by gram-negative bacteria to eliminate neighboring microbes. T6SS plays a pivotal role as a virulence factor, enabling pathogenic gram-negative bacteria to compete with the established communities to colonize hosts and induce infections. Gaining a deeper understanding of bacterial interactions will allow the development of strategies to control the action of systems such as the T6SS that can manipulate bacterial communities. In this context, we demonstrate that bacteria targeted by T6SS attacks from the enteric pathogen Cronobacter malonaticus, which poses a significant threat to infants, can develop a collective protective mechanism centered on the production of type I fimbriae. These adhesive structures promote the aggregation of bacterial preys and the formation of microcolonies, which protect the cells from T6SS attacks.

Synthetic Colonic Mucus Enables the Development of Modular Microbiome Organoids.

The human colon is home to trillions of microorganisms that modulate gastrointestinal physiology. Our understanding of how this gut ecosystem impacts human health, although evolving, has been slowed by the lack of accessible tools suitable to studying complex host-mucus-microbe interactions. Here, we report a synthetic gel-like material capable of recapitulating the varied structural, mechanical, and biochemical profiles of native human colonic mucus to develop compositionally simple microbiome screening platforms with utility in microbiology and drug discovery. The viscous fibrillar material is realized through templated assembly of a fluorine-rich amino acid at liquid-liquid interphases. The fluorine-assisted mucus surrogate (FAMS) can be decorated with mucins to serve as a habitat for microbial colonization and integrated with human colorectal cells to generate artificial mucosae, referred to as a microbiome organoid. Notably, FAMS are made with inexpensive and commercially available materials, and can be generated using simple protocols and standard laboratory hardware. As a result, this platform can be broadly incorporated into various laboratory settings to advance probiotic research and inform in vivo approaches. If implemented into high throughput screening approaches, FAMS may represent a valuable tool to study compound metabolism and gut permeability, with an exemplary demonstration of this utility presented here.

ClusterFinder: a fast tool to find cluster structures from pair distribution function data.

A novel automated high-throughput screening approach, ClusterFinder, is reported for finding candidate structures for atomic pair distribution function (PDF) structural refinements. Finding starting models for PDF refinements is notoriously difficult when the PDF originates from nanoclusters or small nanoparticles. The reported ClusterFinder algorithm can screen 104 to 105 candidate structures from structural databases such as the Inorganic Crystal Structure Database (ICSD) in minutes, using the crystal structures as templates in which it looks for atomic clusters that result in a PDF similar to the target measured PDF. The algorithm returns a rank-ordered list of clusters for further assessment by the user. The algorithm has performed well for simulated and measured PDFs of metal-oxido clusters such as Keggin clusters. This is therefore a powerful approach to finding structural cluster candidates in a modelling campaign for PDFs of nanoparticles and nanoclusters.

High-throughput computational screening of MOF adsorbents for efficient propane capture from air and natural gas mixtures.

In this study, we used a high-throughput computational screening approach to examine the potential of metal-organic frameworks (MOFs) for capturing propane (C3H8) from different gas mixtures. We focused on Quantum MOF (QMOF) database composed of both synthesized and hypothetical MOFs and performed Grand Canonical Monte Carlo (GCMC) simulations to compute C3H8/N2/O2/Ar and C3H8/C2H6/CH4 mixture adsorption properties of MOFs. The separation of C3H8 from air mixture and the simultaneous separation of C3H8 and C2H6 from CH4 were studied for six different adsorption-based processes at various temperatures and pressures, including vacuum-swing adsorption (VSA), pressure-swing adsorption (PSA), vacuum-temperature swing adsorption (VTSA), and pressure-temperature swing adsorption (PTSA). The results of molecular simulations were used to evaluate the MOF adsorbents and the type of separation processes based on selectivity, working capacity, adsorbent performance score, and regenerability. Our results showed that VTSA is the most effective process since many MOFs offer high regenerability (>90%) combined with high C3H8 selectivity (>7 × 103) and high C2H6 + C3H8 selectivity (>100) for C3H8 capture from air and natural gas mixtures, respectively. Analysis of the top MOFs revealed that materials with narrow pores (<10Å) and low porosities (<0.7), having aromatic ring linkers, alumina or zinc metal nodes, typically exhibit a superior C3H8 separation performance. The top MOFs were shown to outperform commercial zeolite, MFI for C3H8 capture from air, and several well-known MOFs for C3H8 capture from natural gas stream. These results will direct the experimental efforts to the most efficient C3H8 capture processes by providing key molecular insights into selecting the most useful adsorbents.

A novel core-shell up-conversion nanoparticles immunochromatographic assay for the detection of deoxynivalenol in cereals

Deoxynivalenol (DON) toxin is a type B group of trichothecene mycotoxins mainly originating from specific Fusarium fungi, seriously harming human and livestock health. Herein, a novel core-shell up-conversion nanoparticles immunochromatographic assay (CS-UCNPs-ICA) was developed for deoxynivalenol based on the competitive reaction principle. By exploiting the fluorescence intensity of the T and C lines of CS-UCNPs-ICA, the concentrations of DON were obtained sensitively and precisely under optimized conditions in 5 min with a detection limit of 0.1 ng/mL. The CS-UCNPs-ICA strips only specifically detect DON and its derivatives (3-Ac-DON and 15-Ac-DON), with no cross-reaction with other mycotoxins. The low CV values illustrated a modest intra- and inter-assay variation, confirming the superior precision of this method. In the spiked experiment, the mean recoveries of corn and wheat ranged from 94.74% to 100.90% and 96.21%–104.81%, respectively. Furthermore, the approach generated results that were in good agreement with data from HPLC and ELISA analyses of naturally contaminated feed and cereals, confirming that the significant advantages of proposed strips were their high practicality, rapidness, and simplicity. Therefore, the CS-UCNPs-ICA strips platform serves as a promising candidate for developing new approaches for rapid testing or high throughput screening from DON in food products.

Biosensor-assisted CRISPRi high-throughput screening to identify genetic targets in Zymomonas mobilis for high d-lactate production

Lactate is an important monomer for the synthesis of poly-lactate (PLA), which is a substitute for the petrochemical plastics. To achieve the goal of high lactate titer, rate, and yield for commercial production, efficient lactate production pathway is needed as well as genetic targets that affect high lactate production and tolerance. In this study, an LldR-based d-lactate biosensor with a broad dynamic range was first applied into Zymomonas mobilis to select mutant strains with strong GFP fluorescence, which could be the mutant strains with increased d-lactate production. Then, LldR-based d-lactate biosensor was combined with a genome-wide CRISPR interference (CRISPRi) library targeting the entire genome to generate thousands of mutants with gRNA targeting different genetic targets across the whole genome. Specifically, two mutant libraries were selected containing 105 and 104 mutants with different interference sites from two rounds of fluorescence-activated cell sorting (FACS), respectively. Two genetic targets of ZMO1323 and ZMO1530 were characterized and confirmed to be associated with the increased d-lactate production, further knockout of ZMO1323 and ZMO1530 resulted in a 15% and 21% increase of d-lactate production, respectively. This work thus not only established a high-throughput approach that combines genome-scale CRISPRi and biosensor-assisted screening to identify genetic targets associated with d-lactate production in Z. mobilis, but also provided a feasible high-throughput screening approach for rapid identification of genetic targets associated with strain performance for other industrial microorganisms.

A high-throughput target-based screening approach for the identification and assessment of Mycobacterium tuberculosis mycothione reductase inhibitors.

The growing anti-microbial resistance poses a global public health threat, impeding progress toward eradicating tuberculosis. Despite decades of active research, there is still a dire need for the discovery of drugs with novel modes of action and exploration of combination drug regimens. Within the European RespiriTB consortium, we explore Mycobacterium tuberculosis energy metabolism to identify new drug candidates that synergize with bedaquiline, with the aim of discovering more efficient combination drug regimens. In this study, we present the development of a high-throughput screening pipeline that led to the identification of M. tuberculosis mycothione reductase inhibitors.

Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer

Numerical simulation of fluid flow plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expands our understanding of various natural and engineered systems. The calculation of heat transfer in fluid flow in simple flat channels is a relatively easy task for various simulation methods. However, once the channel geometry becomes more complex, numerical simulations become a bottleneck in optimizing wall geometries. We present a combination of accurate numerical simulations of arbitrary, flat, and non-flat channels as well as machine learning models trained on simulated data to predict the drag coefficient and Stanton number. We show that convolutional neural networks (CNNs) can accurately predict target properties at a fraction of the computational cost of numerical simulations. We use CNN models in a virtual high-throughput screening approach to explore a large number of possible, randomly generated wall architectures. Data augmentation techniques are incorporated to enforce physical invariances toward shifting and flipping, contributing to precise prediction for fluid flow and heat transfer characteristics. Moreover, we approach the interpretation of the trained model to better understand relevant channel structures and their influence on heat transfer. The general approach is not only applicable to simple flow setups as presented here but can be extended to more complex tasks, such as multiphase or even reactive unit operations in chemical engineering.

Data-Driven Battery Characterization and Prognosis: Recent Progress, Challenges, and Prospects.

Battery characterization and prognosis are essential for analyzing underlying electrochemical mechanisms and ensuring safe operation, especially with the assistance of superior data-driven artificial intelligence systems. This review provides a unique perspective on recent progress in data-driven battery characterization and prognosis methods. First, recent informative image characterization and impedance spectrum as well as high-throughput screening approaches on revealing battery electrochemical mechanisms at multiple scales are summarized. Thereafter, battery prognosis tasks and strategies are described, with the comparison of various physics-informed modeling strategies. Considering unlocking mechanisms from tremendous battery data, the dominant role of physics-informed interpretable learning in accelerating energy device development is presented. Finally, challenges and prospects on data-driven characterization and prognosis are discussed toward accelerating energy device development with much-enhanced electrochemical transparency and generalization. This review is hoped to supply new ideas and inspirations to the next-generation battery development.