Single-cell multi-omics analysis identifies context-specific gene regulatory gates and mechanisms.

There is a growing interest in inferring context specific gene regulatory networks from single-cell RNA sequencing (scRNA-seq) data. This involves identifying the regulatory relationships between transcription factors (TFs) and genes in individual cells, and then characterizing these relationships at the level of specific cell types or cell states. In this study, we introduce scGATE (single-cell gene regulatory gate) as a novel computational tool for inferring TF-gene interaction networks and reconstructing Boolean logic gates involving regulatory TFs using scRNA-seq data. In contrast to current Boolean models, scGATE eliminates the need for individual formulations and likelihood calculations for each Boolean rule (e.g. AND, OR, XOR). By employing a Bayesian framework, scGATE infers the Boolean rule after fitting the model to the data, resulting in significant reductions in time-complexities for logic-based studies. We have applied assay for transposase-accessible chromatin with sequencing (scATAC-seq) data and TF DNA binding motifs to filter out non-relevant TFs in gene regulations. By integrating single-cell clustering with these external cues, scGATE is able to infer context specific networks. The performance of scGATE is evaluated using synthetic and real single-cell multi-omics data from mouse tissues and human blood, demonstrating its superiority over existing tools for reconstructing TF-gene networks. Additionally, scGATE provides a flexible framework for understanding the complex combinatorial and cooperative relationships among TFs regulating target genes by inferring Boolean logic gates among them.

Blocking the dopaminergic receptors within the hippocampal dentate gyrus reduced analgesic responses induced by restraint stress in the formalin test.

Previous studies have shown that various receptors, including dopamine receptors, are expressed in the hippocampal dentate gyrus (DG). Besides, indicatively, dopamine receptors play an essential role in the modulation of pain perception. On the other hand, stressful experiences can produce analgesia, termed stress-induced analgesia (SIA). The current study examined the probable role of dopamine receptors within the DG in antinociception induced by restraint stress (RS). Ninety-seven male albino Wistar rats were unilaterally implanted with a cannula in the DG. Animals received intra-DG microinjections of SCH23390 or Sulpiride (0.25, 1, and 4 µg/rat) as D1-and D2-like dopamine receptor antagonists, respectively, five minutes before RS. Ten minutes after the end of the induction of RS for three hours, 50 µl 2.5% formalin was injected subcutaneously into the plantar surface of the hind paw to induce persistent inflammatory pain. Pain scores were evaluated at 5-minute intervals for 60 minutes. These findings showed that; exposure to RS for three hours produced SIA in both phases of the formalin test, while this RS-induced analgesia was attenuated in the early and late phases of the formalin test by intra-DG microinjection of SCH23390 and Sulpiride. The results of the present study suggested that both D1- and D2-like dopamine receptors in the DG have a considerable role in the induced analgesia by RS.

A computational model of stem cells' internal mechanism to recapitulate spatial patterning and maintain the self-organized pattern in the homeostasis state.

The complex functioning of multi-cellular tissue development relies on proper cell production rates to replace dead or differentiated specialized cells. Stem cells are critical for tissue development and maintenance, as they produce specialized cells to meet the tissues' demands. In this study, we propose a computational model to investigate the stem cell's mechanism, which generates the appropriate proportion of specialized cells, and distributes them to their correct position to form and maintain the organized structure in the population through intercellular reactions. Our computational model focuses on early development, where the populations overall behavior is determined by stem cells and signaling molecules. The model does not include complicated factors such as movement of specialized cells or outside signaling sources. The results indicate that in our model, the stem cells can organize the population into a desired spatial pattern, which demonstrates their ability to self-organize as long as the corresponding leading signal is present. We also investigate the impact of stochasticity, which provides desired non-genetic diversity; however, it can also break the proper boundaries of the desired spatial pattern. We further examine the role of the death rate in maintaining the system's steady state. Overall, our study sheds light on the strategies employed by stem cells to organize specialized cells and maintain proper functionality. Our findings provide insight into the complex mechanisms involved in tissue development and maintenance, which could lead to new approaches in regenerative medicine and tissue engineering.

Contribution of the intra-hippocampal orexin system in the regulation of restraint stress response to pain-related behaviors in the formalin test.

Stress-induced antinociception (SIA) is due to the activation of several neural pathways and neurotransmitters that often suppress pain perception. Studies have shown that the orexin neuropeptide system is essential in pain modulation. Therefore, this study aimed to investigate the role of orexinergic receptors in the hippocampal CA1 region in modulating SIA response during the formalin test as an animal model of inflammatory pain. The orexin-1 receptor (OX1r) antagonist, SB334867, at 1, 3, 10, and 30 nmol or TCS OX2 29 as an orexin-2 receptor (OX2r) antagonist at the same doses were microinjected into the CA1 region in rats. Five minutes later, rats were exposed to restraint stress (RS) for 3 h, and pain-related behaviors were monitored in 5-min blocks for the 60-min test period in the formalin test. Results showed that applying RS for 3 h reduced pain responses in the early and late phases of the formalin test. The main findings showed that intra-CA1 injection of orexin receptor antagonists reduced the antinociception caused by stress in both phases of the formalin test. In addition, the contribution of OX2r in mediating the antinociceptive effect of stress was more prominent than that of OX1r in the early phase of the formalin test. However, in the late phase, both receptors worked similarly. Accordingly, the orexin system and its two receptors in the CA1 region of the hippocampus regulate SIA response to this animal model of pain in formalin test.

Network-Based and Machine-Learning Approaches Identify Diagnostic and Prognostic Models for EMT-Type Gastric Tumors.

The microsatellite stable/epithelial-mesenchymal transition (MSS/EMT) subtype of gastric cancer represents a highly aggressive class of tumors associated with low rates of survival and considerably high probabilities of recurrence. In the era of precision medicine, the accurate and prompt diagnosis of tumors of this subtype is of vital importance. In this study, we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify a differentially expressed co-expression module of mRNAs in EMT-type gastric tumors. Using network analysis and linear discriminant analysis, we identified mRNA motifs and microRNA-based models with strong prognostic and diagnostic relevance: three models comprised of (i) the microRNAs miR-199a-5p and miR-141-3p, (ii) EVC/EVC2/GLI3, and (iii) PDE2A/GUCY1A1/GUCY1B1 gene expression profiles distinguish EMT-type tumors from other gastric tumors with high accuracy (Area Under the Receiver Operating Characteristic Curve (AUC) = 0.995, AUC = 0.9742, and AUC = 0.9717; respectively). Additionally, the DMD/ITGA1/CAV1 motif was identified as the top motif with consistent relevance to prognosis (hazard ratio > 3). Molecular functions of the members of the identified models highlight the central roles of MAPK, Hh, and cGMP/cAMP signaling in the pathology of the EMT subtype of gastric cancer and underscore their potential utility in precision therapeutic approaches.

wpLogicNet: logic gate and structure inference in gene regulatory networks.

MOTIVATION: The gene regulatory process resembles a logic system in which a target gene is regulated by a logic gate among its regulators. While various computational techniques are developed for a gene regulatory network (GRN) reconstruction, the study of logical relationships has received little attention. Here, we propose a novel tool called wpLogicNet that simultaneously infers both the directed GRN structures and logic gates among genes or transcription factors (TFs) that regulate their target genes, based on continuous steady-state gene expressions. RESULTS: wpLogicNet proposes a framework to infer the logic gates among any number of regulators, with a low time-complexity. This distinguishes wpLogicNet from the existing logic-based models that are limited to inferring the gate between two genes or TFs. Our method applies a Bayesian mixture model to estimate the likelihood of the target gene profile and to infer the logic gate a posteriori. Furthermore, in structure-aware mode, wpLogicNet reconstructs the logic gates in TF-gene or gene-gene interaction networks with known structures. The predicted logic gates are validated on simulated datasets of TF-gene interaction networks from Escherichia coli. For the directed-edge inference, the method is validated on datasets from E.coli and DREAM project. The results show that compared to other well-known methods, wpLogicNet is more precise in reconstructing the network and logical relationships among genes. AVAILABILITY AND IMPLEMENTATION: The datasets and R package of wpLogicNet are available in the github repository, https://github.com/CompBioIPM/wpLogicNet. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01.

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Removal of Penicillin G from aqueous medium by PPI@SBA-15/ZIF-8 super adsorbent: Adsorption isotherm, thermodynamic, and kinetic studies.

In the present paper, synthesis of SBA-15 nanoparticles was carried out from tetraethyl orthosilicate (TEOS) precursor using the sol-gel process. After being combined with Poly propylene imine, and ZIF-8 they were employed for the removal of Penicillin G. The synthesized combination morphology was assessed using nitrogen adsorption and desorption (BET), Fourier transform infrared (FTIR) spectroscopy, and X-ray powder diffraction (XRD). The parameters affecting Penicillin G removal, including pH, amount of adsorbent, time of contact, temperature, and concentration, were optimized, and the optimum levels of the mentioned variables were reported to be pH = 3, 0.03 g, 90 min, 25 °C, and 100 ppm, respectively. In addition, application of Freundlich, Langmuir, Dubinin-Radushkevhch, and Tempkin models and pseudo-first-order and pseudo-second-order adsorption synthetic equations aimed at determining the type of adsorbent isotherm. The results showed that the best fitting of Langmuir (R2 = 0.9944, qm = 400 mg/g) for adsorption isotherm and pseudo-second-order model (R2 = 0.9905) for kinetics studies. Furthermore, data of Gibbs free energy and enthalpy demonstrated an exothermic and spontaneous process in the research.

Effect of asymptomatic transmission and emergence time on multi-strain viral disease severity.

In a viral epidemic, the emergence of a novel strain with increased transmissibility (larger value of basic reproduction number R0) sparks the fear that the increase in transmissibility is likely to lead to an increase in disease severity. It is required to investigate if a new, more contagious strain will be necessarily dominant in the population and resulting in more disease severity. In this paper, the impact of the asymptomatic transmission and the emergence time of a more transmissible variant of a multi-strain viral disease on the disease prevalence, disease severity, and the dominant variant in an epidemic was investigated by a proposed 2-strain epidemic model. The simulation results showed that considering only R0, is insufficient to predict the outcome of a new, more contagious strain in the population. A more transmissible strain with a high fraction of asymptomatic cases can substantially reduce the mortality rate. If the emergence time of the new strain is closer to the start of the epidemic, the new, more contagious variant has more chance to win the viral competition and be the dominant strain; otherwise, despite being more contagious, it cannot dominate previous strains. In conclusion, three factors of R0, the fraction of asymptomatic transmission, and the emergence time of the new strain are required to correctly determine the prevalence, disease severity, and the winner of the viral competition.

Identification of UBA1 as the causative gene of an X-linked non-Kennedy spinal-bulbar muscular atrophy.

BACKGROUND AND PURPOSE: Spinal-bulbar muscular atrophy (SBMA) (Kennedy's disease) is a motor neuron disease. Kennedy's disease is nearly exclusively caused by mutations in the androgen receptor encoding gene (AR). The results of studies aimed at identification of the genetic cause of a disease that best approximates SBMA in a pedigree (four patients) without mutations in AR are reported. METHODS: Clinical investigations included thorough neurological and non-neurological examinations and testing. Genetic analysis was performed by exome sequencing using standard protocols. UBA1 mutations were modeled on the crystal structure of UBA1. RESULTS: The clinical features of the patients are described in detail. A missense mutation in UBA1 (c.T1499C; p.Ile500Thr) was identified as the probable cause of the non-Kennedy SBMA in the pedigree. Like AR, UBA1 is positioned on chromosome X. UBA1 is a highly conserved gene. It encodes ubiquitin-like modifier activating enzyme 1 (UBA1) which is the major E1 enzyme of the ubiquitin-proteasome system. Interestingly, UBA1 mutations can also cause infantile-onset X-linked spinal muscular atrophy (XL-SMA). The mutation identified here and the XL-SMA causative mutations were shown to affect amino acids positioned in the vicinity of UBA1's ATP binding site and to cause structural changes. CONCLUSION: UBA1 was identified as a novel SBMA causative gene. The gene affects protein homeostasis which is one of most important components of the pathology of neurodegeneration. The contribution of this same gene to the etiology of XL-SMA is discussed.

A computational model of stem cells' decision-making mechanism to maintain tissue homeostasis and organization in the presence of stochasticity.

The maintenance of multi-cellular developed tissue depends on the proper cell production rate to replace the cells destroyed by the programmed process of cell death. The stem cell is the main source of producing cells in a developed normal tissue. It makes the stem cell the lead role in the scene of a fully formed developed tissue to fulfill its proper functionality. By focusing on the impact of stochasticity, here, we propose a computational model to reveal the internal mechanism of a stem cell, which generates the right proportion of different types of specialized cells, distribute them into their right position, and in the presence of intercellular reactions, maintain the organized structure in a homeostatic state. The result demonstrates that the spatial pattern could be harassed by the population geometries. Besides, it clearly shows that our model with progenitor cells able to recover the stem cell presence could retrieve the initial pattern appropriately in the case of injury. One of the fascinating outcomes of this project is demonstrating the contradictory roles of stochasticity. It breaks the proper boundaries of the initial spatial pattern in the population. While, on the flip side of the coin, it is the exact factor that provides the demanded non-genetic diversity in the tissue. The remarkable characteristic of the introduced model as the stem cells' internal mechanism is that it could control the overall behavior of the population without need for any external factors.

A randomized controlled clinical trial of the effects of range of motion exercises and massage on muscle strength in critically ill patients.

BACKGROUND: Atrophy and muscle weakness is a common problem in critically ill patients admitted to the intensive care unit (ICU). Muscle weakness in severe cases can lead to tetraplegia, reduced or lost tendon reflexes, delayed weaning from mechanical ventilation, physical disability, and increased mortality. The aim of this study was to compare the effects of range of motion exercises (ROM) and massage on muscle strength of the patients admitted to ICUs. METHODS: This study was a single-blinded randomized controlled trial conducted in ICUs of Afzalipour hospital in Kerman, southeastern Iran. Ninety conscious ICU patients were randomly divided into three groups (massage, ROM exercises and control). The researcher/co-researcher massaged or did ROM exercises on the patients' extremities once a day for seven consecutive days. Using a hand-held dynamometer, the co-researcher, rated the muscle strength before, on the fourth and seventh days of intervention at 8 p.m. RESULTS: The mean muscles strength of the right arm in the ROM exercise and massage groups increased by 0.63 kg, and 0.29 kg, respectively after the intervention compared with before the intervention. The muscle strength of the right arm in the control group reduced by 0.55 kg. The mean muscles strength of the left arm in the ROM exercise and massage groups increased by 0.61 kg and 0.28 kg after the intervention, respectively while it reduced by 0.56 kg in the control group. The mean muscles strength of the right leg in the ROM exercise and massage groups increased by 0.53 kg and 0.27 kg after the intervention compared with before the intervention while it reduced by 0.70 kg in the control group. The mean muscles strength of the left leg in the ROM exercise and massage groups increased by 0.54 kg and 0.26 kg after the intervention compared with before the intervention while it reduced by 0.71 kg in the control group. CONCLUSION: The results of the present study showed that ROM exercises and massage were effective interventions in increasing muscle strength of the critically ill patients admitted to intensive care units.

Determining the adjusted initial treatment dose of warfarin anticoagulant medicine using kernel-based support vector regression.

BACKGROUND AND OBJECTIVE: A novel research field in bioinformatics is pharmacogenomics and the corresponding applications of artificial intelligence tools. Pharmacogenomics is the study of the relationship between genotype and responses to medical measures such as drug use. One of the most effective drugs is warfarin anticoagulant, but determining its initial treatment dose is challenging. Mistakes in the determination of the initial treatment dose can result directly in patient death. METHODS: Some of the most successful techniques for estimating the initial treatment dose are kernel-based methods. However, all the available studies use pre-defined and constant kernels that might not necessarily address the problem's intended requirements. The present study seeks to define and present a new computational kernel extracted from a data set. This process aims to utilize all the data-related statistical features to generate a dose determination tool proportional to the data set with minimum error rate. The kernel-based version of the least square support vector regression estimator was defined. Through this method, a more appropriate approach was proposed for predicting the adjusted dose of warfarin. RESULTS AND CONCLUSION: This paper benefits from the International Warfarin Pharmacogenomics Consortium (IWPC) Database. The results obtained in this study demonstrate that the support vector regression with the proposed new kernel can successfully estimate the ideal dosage of warfarin for approximately 68% of patients.

Prospects and challenges of cancer systems medicine: from genes to disease networks.

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Reactive/Less-cooperative individuals advance population's synchronization: Modeling of Dictyostelium discoideum concerted signaling during aggregation phase.

Orchestrated chemical signaling of single cells sounds to be a linchpin of emerging organization and multicellular life form. The social amoeba Dictyostelium discoideum is a well-studied model organism to explore overall pictures of grouped behavior in developmental biology. The chemical waves secreted by aggregating Dictyostelium is a superb example of pattern formation. The waves are either circular or spiral in shape, according to the incremental population density of a self-aggregating community of individuals. Here, we revisit the spatiotemporal patterns that appear in an excitable medium due to synchronization of randomly firing individuals, but with a more parsimonious attitude. According to our model, a fraction of these individuals are less involved in amplifying external stimulants. Our simulations indicate that the cells enhance the system's asymmetry and as a result, nucleate early sustainable spiral territory zones, provided that their relative population does not exceed a tolerable threshold.

Population-level heterogeneity as a reflection of mixed strategy: A computational perspective on the Crabtree effect.

Is population-level heterogeneity a reflection of distinct subpopulations, exhibiting different metabolic functions, or dynamic metabolism of individuals within the population? This fascinating question has remained a subject of great interest in studying metabolic specialization in microorganisms. The Crabtree effect - i.e., the ability of some microorganisms to switch from respiration to fermentation in the presence of oxygen - is an appropriate case study to address the aforementioned question. Game-theoretical approaches have been routinely used to examine and explain the way a microorganism, such as yeast, would switch between the two ATP-producing pathways, i.e., respiration and fermentation. Here we attempt to explain the switch between respiration and fermentation in yeast by constructing a simple metabolic switch. We then utilize an individual-based model, in which each individual is equipped with all the relevant chemical reactions, to see how cells equipped with such metabolic switch would behave in different conditions. We further investigate our proposed metabolic switch using the game-theoretical approach. Based on this model, we postulate that the population-level metabolic heterogeneity in microorganisms can simply arise from individuals utilizing a mixed strategy.

Network analysis and the impact of Aflibercept on specific mediators of angiogenesis in HUVEC cells.

Angiogenesis, inflammation and endothelial cells' migration and proliferation exert fundamental roles in different diseases. However, more studies are needed to identify key proteins and pathways involved in these processes. Aflibercept has received the approval of the US Food and Drug Administration (FDA) for the treatment of wet AMD and colorectal cancer. Moreover, the effect of Aflibercept on VEGFR2 downstream signalling pathways has not been investigated yet. Here, we integrated text mining data, protein-protein interaction networks and multi-experiment microarray data to specify candidate genes that are involved in VEGFA/VEGFR2 signalling pathways. Network analysis of candidate genes determined the importance of the nominated genes via different centrality parameters. Thereupon, several genes-with the highest centrality indexes-were recruited to investigate the impact of Aflibercept on their expression pattern in HUVEC cells. Real-time PCR was performed, and relative expression of the specific genes revealed that Aflibercept modulated angiogenic process by VEGF/PI3KA/AKT/mTOR axis, invasion by MMP14/MMP9 axis and inflammation-related angiogenesis by IL-6-STAT3 axis. Data showed Aflibercept simultaneously affected these processes and determined the nominated axes that had been affected by the drug. Furthermore, integrating the results of Aflibercept on expression of candidate genes with the current network analysis suggested that resistance against the Aflibercept effect is a plausible process in HUVEC cells.

Orexin-2 receptor antagonism in the cornu ammonis 1 region of hippocampus prevented the antinociceptive responses induced by chemical stimulation of the lateral hypothalamus in the animal model of persistent pain.

Orexins are excitatory neuropeptides, mainly produced by neurons located in the lateral hypothalamus, which project to many brain areas. The orexinergic system plays a fundamental role in arousal, sleep/wakefulness, feeding, energy homeostasis, motivation, reward, stress and pain modulation. As a prominent part of the limbic system, the hippocampus has been involved in formalin-induced nociception modulation. Moreover, hippocampus regions express both orexin-1 (OX1) and orexin-2 (OX2) receptors. The present study investigated the role of OX2 receptors (OX2R) within the cornu ammonis 1 (CA1) region of the hippocampus in the mediation of lateral hypothalamus-induced antinociception. Fifty-three male Wistar rats were unilaterally implanted with two separate cannulae into the lateral hypothalamus and CA1. Animals were pretreated with intra-CA1 TCS OX2 29 as an OX2R antagonist before intra-lateral hypothalamus administration of carbachol (250 nM) as a muscarinic agonist for chemical stimulation of orexinergic neurons. Formalin test was used as an animal model of persistent pain, following intra-lateral hypothalamus carbachol microinjection. Results showed that the chemical stimulation of the lateral hypothalamus significantly attenuated formalin-evoked nociceptive behaviors during both phases of the formalin test, and administration of TCS OX2 29 into the CA1 blocked these antinociceptive responses in both phases, especially in the late phase. These findings suggest that OX2 receptors in the CA1 partially mediate the lateral hypothalamus-induced antinociceptive responses in persistent inflammatory pain.

False Negative Mitigation in Group Testing for COVID-19 Screening.

After lifting the COVID-19 lockdown restrictions and opening businesses, screening is essential to prevent the spread of the virus. Group testing could be a promising candidate for screening to save time and resources. However, due to the high false-negative rate (FNR) of the RT-PCR diagnostic test, we should be cautious about using group testing because a group's false-negative result identifies all the individuals in a group as uninfected. Repeating the test is the best solution to reduce the FNR, and repeats should be integrated with the group-testing method to increase the sensitivity of the test. The simplest way is to replicate the test twice for each group (the 2Rgt method). In this paper, we present a new method for group testing (the groupMix method), which integrates two repeats in the test. Then we introduce the 2-stage sequential version of both the groupMix and the 2Rgt methods. We compare these methods analytically regarding the sensitivity and the average number of tests. The tradeoff between the sensitivity and the average number of tests should be considered when choosing the best method for the screening strategy. We applied the groupMix method to screening 263 people and identified 2 infected individuals by performing 98 tests. This method achieved a 63% saving in the number of tests compared to individual testing. Our experimental results show that in COVID-19 screening, the viral load can be low, and the group size should not be more than 6; otherwise, the FNR increases significantly. A web interface of the groupMix method is publicly available for laboratories to implement this method.