Designing glucose utilization "highway" for recombinant biosynthesis.

cAMP receptor protein (CRP) is known as a global regulatory factor mainly mediating carbon source catabolism. Herein, we successfully engineered CRP to develop microbial chassis cells with improved recombinant biosynthetic capability in minimal medium with glucose as single carbon source. The obtained best-performing cAMP-independent CRPmu9 mutant conferred both faster cell growth and a 133-fold improvement in expression level of lac promoter in presence of 2% glucose, compared with strain under regulation of CRPwild-type. Promoters free from "glucose repression" are advantageous for recombinant expression, as glucose is a frequently used inexpensive carbon source in high-cell-density fermentations. Transcriptome analysis demonstrated that the CRP mutant globally rewired cell metabolism, displaying elevated tricarboxylic acid cycle activity; reduced acetate formation; increased nucleotide biosynthesis; and improved ATP synthesis, tolerance, and stress-resistance activity. Metabolites analysis confirmed the enhancement of glucose utilization with the upregulation of glycolysis and glyoxylate-tricarboxylic acid cycle. As expected, an elevated biosynthetic capability was demonstrated with vanillin, naringenin and caffeic acid biosynthesis in strains regulated by CRPmu9. This study has expanded the significance of CRP optimization into glucose utilization and recombinant biosynthesis, beyond the conventionally designated carbon source utilization other than glucose. The Escherichiacoli cell regulated by CRPmu9 can be potentially used as a beneficial chassis for recombinant biosynthesis.

Rapid detection of SARS-CoV-2 with CRISPR-Cas12a.

The recent outbreak of betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is responsible for the Coronavirus Disease 2019 (COVID-19) global pandemic, has created great challenges in viral diagnosis. The existing methods for nucleic acid detection are of high sensitivity and specificity, but the need for complex sample manipulation and expensive machinery slow down the disease detection. Thus, there is an urgent demand to develop a rapid, inexpensive, and sensitive diagnostic test to aid point-of-care viral detection for disease monitoring. In this study, we developed a clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated proteins (Cas) 12a-based diagnostic method that allows the results to be visualized by the naked eye. We also introduced a rapid sample processing method, and when combined with recombinase polymerase amplification (RPA), the sample to result can be achieved in 50 minutes with high sensitivity (1-10 copies per reaction). This accurate and portable detection method holds a great potential for COVID-19 control, especially in areas where specialized equipment is not available.

Two-stage deep learning method for sparse-view fluorescence molecular tomography reconstruction.

Fluorescence molecular tomography (FMT) is a preclinical optical tomographic imaging technique that can trace various physiological and pathological processes at the cellular or even molecular level. Reducing the number of FMT projection views can improve the data acquisition speed, which is significant in applications such as dynamic problems. However, a reduction in the number of projection views will dramatically aggravate the ill-posedness of the FMT inverse problem and lead to significant degradation of the reconstructed images. To deal with this problem, we have proposed a deep-learning-based reconstruction method for sparse-view FMT that only uses four perpendicular projection views and divides the image reconstruction into two stages: image restoration and inverse Radon transform. In the first stage, the projection views of the surface fluorescence are restored to eliminate the blur derived from photon diffusion through a fully convolutional neural network. In the second stage, another convolutional neural network is used to implement the inverse Radon transform between the restored projections from the first stage and the reconstructed transverse slices. Numerical simulation and phantom and mouse experiments are carried out. The results show that the proposed method can effectively deal with the image reconstruction problem of sparse-view FMT.

Image restoration for blurry optical images caused by photon diffusion with deep learning.

Optical macroscopic imaging techniques have shown great significance in the investigations of biomedical issues by revealing structural or functional information of living bodies through the detection of visible or near-infrared light derived from different mechanisms. However, optical macroscopic imaging techniques suffer from poor spatial resolution due to photon diffusion in biological tissues. This dramatically restricts the application of optical imaging techniques in numerous situations. In this paper, an image restoration method based on deep learning is proposed to eliminate the blur caused by photon diffusion in optical macroscopic imaging. Two blurry images captured at orthogonal angles are used as the additional information to ensure the uniqueness of the solution and restore the small targets at deep locations. Then a fully convolutional neural network is proposed to accomplish the image restoration, which consists of three sectors: V-shaped network for central view, V-shaped network for side views, and synthetical path. The two V-shaped networks are concatenated to the synthetical path with skip connections to generate the output image. Simulations as well as phantom and mouse experiments are implemented. Results indicate the effectiveness of the proposed method.

Rapid Screening of Bimetallic Electrocatalysts Using Single Nanoparticle Collision Electrochemistry.

The pace of nanomaterial discovery for high-performance electrocatalysts could be accelerated by the development of efficient screening methods. However, conventional electrochemical characterization via drop-casting is inherently inaccurate and time-consuming, as such ensemble measurements are serially performed through nanocatalyst synthesis, morphological characterization, and performance testing. Herein, we propose a rapid electrochemical screening method for bimetallic electrocatalysts that combines nanoparticle (NP) preparation and performance testing at the single NP level, thus avoiding any inhomogeneous averaging contribution. We employed single NP collision electrochemistry to realize in situ electrodeposition of a precisely tunable Pt shell onto individual parent NPs, followed by instantaneous electrocatalytic measurement of the newborn bimetallic core-shell NPs. We demonstrated the utility of this approach by screening bimetallic Au-Pt NPs and Ag-Pt NPs, thereby exhibiting promising electrocatalytic activity at optimal atomic ratios for methanol oxidation and oxygen reduction reactions, respectively. This work provides a new insight for the rapid screening of other bimetallic electrocatalysts.

Dynamic control of toxic natural product biosynthesis by an artificial regulatory circuit.

To mimic the delicately regulated metabolism in nature for improved efficiency, artificial and customized regulatory components for dynamically controlling metabolic networks in multiple layers are essential in laboratory engineering. For this purpose, a novel regulatory component for controlling vanillin biosynthetic pathway was developed through directed evolution, which was responsive to both the product vanillin and substrate ferulic acid, with different capacities. This regulatory component facilitated pathway expression via dynamic control of the intracellular substrate and product concentrations. As vanillin is an antimicrobial compound, low pathway expression and vanillin formation levels enabled better cell growth at an early stage, and the product feedback-activated pathway expression at later stages significantly improved biosynthesis efficiency. This novel multiple-layer dynamic control was demonstrated effective in managing the trade-off between cell growth and production, leading to improved cell growth and vanillin production compared to the conventional or quorum-sensing promoter-controlled pathway. The multiple-layer dynamic control enabled by designed regulatory components responsive to multiple signals shows potential for wide applications in addition to the dynamic controls based on biosynthetic intermediate sensing and quorum sensing reported to date.

Bi2O3-Sensitized TiO2 Hollow Photocatalyst Drives the Efficient Removal of Tetracyclines under Visible Light.

The complete removal of tetracycline residuals under visible light still is a challenging task because of their robust ring structure. To tackle this issue, we explore a novel Bi2O3-sensitized TiO2 visible-light photocatalyst by combining p-n heterojunction with hollow structure. The hollow TiO2/Bi2O3 photocatalyst manifests excellent photocatalytic performance and recyclability toward the complete degradation (100%) of antibiotics under visible light (λ > 420 nm) because of the synergistic effect of p-n heterojunction and hollow structure, successfully overcoming the challenge of the incomplete removal of antibiotics over almost all of the reported visible-light photocatalysts. Additionally, the effects of inorganic ions, pH value, water matrix, and outdoor light on the degradation of tetracyclines were investigated with many details. Notably, the degradation pathways and mechanism of tetracycline were revealed according to trapping experiments, HPLC-MS, and photoelectrochemical characterizations. Therefore, this work provides a new insight into developing visible-light photocatalysts with excellent photocatalytic performances for the complete removal of other refractory contaminants.

The BET bromodomain inhibitor apabetalone induces apoptosis of latent HIV-1 reservoir cells following viral reactivation.

The persistence of latent HIV-1 reservoirs throughout combination antiretroviral therapy (cART) is a major barrier on the path to achieving a cure for AIDS. It has been shown that bromodomain and extra-terminal (BET) inhibitors could reactivate HIV-1 latency, but restrained from clinical application due to their toxicity and side effects. Thus, identifying a new type of BET inhibitor with high degrees of selectivity and safety is urgently needed. Apabetalone is a small-molecule selective BET inhibitor specific for second bromodomains, and has been evaluated in phase III clinical trials that enrolled patients with high-risk cardiovascular disorders, dyslipidemia, and low HDL cholesterol. In the current study, we examined the impact of apabetalone on HIV-1 latency. We showed that apabetalone (10-50 µmol/L) dose-dependently reactivated latent HIV-1 in 4 types of HIV-1 latency cells in vitro and in primary human CD4+ T cells ex vivo. In ACH2 cells, we further demonstrated that apabetalone activated latent HIV-1 through Tat-dependent P-TEFB pathway, i.e., dissociating bromodomain 4 (BDR4) from the HIV-1 promoter and recruiting Tat for stimulating HIV-1 elongation. Furthermore, we showed that apabetalone (10-30 µmol/L) caused dose-dependent cell cycle arrest at the G1/G0 phase in ACH2 cells, and thereby induced the preferential apoptosis of HIV-1 latent cells to promote the death of reactivated reservoir cells. Notably, cardiovascular diseases and low HDL cholesterol are known as the major side effects of cART, which should be prevented by apabetalone. In conclusion, apabetalone should be an ideal bifunctional latency-reversing agent for advancing HIV-1 eradication and reducing the side effects of BET inhibitors.

Engineering the effector specificity of regulatory proteins for the in vitro detection of biomarkers and pesticide residues.

Transcriptional regulatory proteins (TRPs)-based whole-cell biosensors are promising owing to their specificity and sensitivity, but their applications are currently limited. Herein, TRPs were adapted for the extracellular detection of a disease biomarker, uric acid, and a typical pesticide residue, carbaryl. A mutant regulatory protein that specifically recognizes carbaryl as its non-natural effector and activates transcription upon carbaryl binding was developed by engineering the regulatory protein TtgR from Pseudomonas putida. The TtgR mutant responsive to carbaryl and a regulatory protein responsive to uric acid were used for in vitro detection, based on their allosteric binding of operator DNA and inducer molecules. Based on the quantitative polymerase chain reactions (qPCRs) output, the minimum detectable concentration was between 1 nM-1 µM and 1-10 nM for uric acid and carbaryl, respectively. Our results demonstrated that engineering the effector specificity of regulatory proteins is a potential technique for generating molecular recognition elements for not only in vivo but also in vitro applications.

Myricetin antagonizes semen-derived enhancer of viral infection (SEVI) formation and influences its infection-enhancing activity.

BACKGROUND: Semen is a critical vector for human immunodeficiency virus (HIV) sexual transmission and harbors seminal amyloid fibrils that can markedly enhance HIV infection. Semen-derived enhancer of viral infection (SEVI) is one of the best-characterized seminal amyloid fibrils. Due to their highly cationic properties, SEVI fibrils can capture HIV virions, increase viral attachment to target cells, and augment viral fusion. Some studies have reported that myricetin antagonizes amyloid ß-protein (Aß) formation; myricetin also displays strong anti-HIV activity in vitro. RESULTS: Here, we report that myricetin inhibits the formation of SEVI fibrils by binding to the amyloidogenic region of the SEVI precursor peptide (PAP248-286) and disrupting PAP248-286 oligomerization. In addition, myricetin was found to remodel preformed SEVI fibrils and to influence the activity of SEVI in promoting HIV-1 infection. Moreover, myricetin showed synergistic effects against HIV-1 infection in combination with other antiretroviral drugs in semen. CONCLUSIONS: Incorporation of myricetin into a combination bifunctional microbicide with both anti-SEVI and anti-HIV activities is a highly promising approach to preventing sexual transmission of HIV.

Gamma rays excited radioluminescence tomographic imaging.

BACKGROUND: Radionuclide-excited luminescence imaging is an optical radionuclide imaging strategy to reveal the distributions of radioluminescent nanophosphors (RLNPs) inside small animals, which uses radioluminescence emitted from RLNPs when excited by high energy rays such as gamma rays generated during the decay of radiotracers used in clinical nuclear medicine imaging. Currently, there is no report of tomographic imaging based on radioluminescence. METHODS: In this paper, we proposed a gamma rays excited radioluminescence tomography (GRLT) to reveal three-dimensional distributions of RLNPs inside a small animal using radioluminescence through image reconstruction from surface measurements of radioluminescent photons using an inverse algorithm. The diffusion equation was employed to model propagations of radioluminescent photons in biological tissues with highly scattering and low absorption characteristics. RESULTS: Phantom and artificial source-implanted mouse model experiments were employed to test the feasibility of GRLT, and the results demonstrated that the ability of GRLT to reveal the distribution of RLNPs such as Gd2O2S:Tb using the radioluminescent signals when excited by gamma rays produced from 99mTc. CONCLUSIONS: With the emerging of targeted RLNPs, GRLT can provide new possibilities for in vivo and noninvasive examination of biological processes at cellular levels. Especially, combining with Cerenkov luminescence imaging, GRLT can achieve dual molecular information of RLNPs and nuclides using single optical imaging technology.

A Degraded Fragment of HIV-1 Gp120 in Rat Hepatocytes Forms Fibrils and Enhances HIV-1 Infection.

Identification of the host or viral factors that enhance HIV infection is critical for preventing sexual transmission of HIV. Amyloid fibrils derived from human semen, including semen-derived enhancer of virus infection and semenogelins, enhance HIV-1 infection dramatically in vitro. In this study, we reported that a short-degraded peptide fragment 1 (DPF1) derived from native HIV-1 envelope protein gp120-loaded rat hepatocytes, formed fibrils by self-assembly and thus enhanced HIV-1 infection by promoting the binding of HIV-1 to target cells. Furthermore, DPF1-formed fibrils might be used as a crossing seed to accelerate the formation of semen-derived enhancer of virus infection and semenogelin fibrils. It will be helpful to clarify the viral factors that affect HIV-1 infection. DPF1 as an analog of gp120 containing the critical residues for CD4 binding might be useful for designing of HIV vaccines and developing HIV entry inhibitors.

Reconstruction of fluorescence molecular tomography with a cosinoidal level set method.

BACKGROUND: Implicit shape-based reconstruction method in fluorescence molecular tomography (FMT) is capable of achieving higher image clarity than image-based reconstruction method. However, the implicit shape method suffers from a low convergence speed and performs unstably due to the utilization of gradient-based optimization methods. Moreover, the implicit shape method requires priori information about the number of targets. METHODS: A shape-based reconstruction scheme of FMT with a cosinoidal level set method is proposed in this paper. The Heaviside function in the classical implicit shape method is replaced with a cosine function, and then the reconstruction can be accomplished with the Levenberg-Marquardt method rather than gradient-based methods. As a result, the priori information about the number of targets is not required anymore and the choice of step length is avoided. RESULTS: Numerical simulations and phantom experiments were carried out to validate the proposed method. Results of the proposed method show higher contrast to noise ratios and Pearson correlations than the implicit shape method and image-based reconstruction method. Moreover, the number of iterations required in the proposed method is much less than the implicit shape method. CONCLUSIONS: The proposed method performs more stably, provides a faster convergence speed than the implicit shape method, and achieves higher image clarity than the image-based reconstruction method.

Shape-based reconstruction of dynamic fluorescent yield with a level set method.

BACKGROUND: Fluorescence molecular tomography (FMT) is an optical imaging technique that reveals biological processes within small animals through non-invasively reconstructing the distributions of fluorescent agents. The primary problem in FMT with non-stationary fluorescent yield is the increase of the unknown parameters to be reconstructed. In this paper, a method is proposed to reconstruct dynamic fluorescent yield. METHODS: A shape-based reconstruction method that recovers dynamic fluorescent yield with a level set method is proposed for FMT. To reduce the number of unknown parameters, a level set function is introduced to describe the shape of target and a small number of parameters are used to describe the fluorescent yields at different time points. RESULTS: Results of simulations and phantom experiments demonstrate that the proposed method can recover well the dynamic fluorescent yields, shapes and locations of the target. CONCLUSIONS: The proposed method can handle the cases with non-stationary fluorescent yields and recover the fluorescent yields at each projection angle.

Reconstruction of in vivo fluorophore concentration variation with structural priors and smooth penalty.

Reconstruction of fluorophore concentration variation in fluorescence molecular tomography is expected to reveal the metabolic processes of fluorescent biomarkers in vivo. However, the complicated and strong noise within in vivo data inhibits its applications for in vivo cases. A smooth penalty method is presented in this work to suppress the noise. The method is based on a recursive reconstruction scheme which reconstructs the fluorophore concentration variation rates (FCVRs) of two neighboring frames at the same time within an inner iteration. In addition, the performance of the Laplacian-type regularization incorporating structural priors is investigated. Results of simulations suggest that the smooth penalty method almost has no influence on the reconstructed FCVRs when the target curve is smooth, and results of in vivo experiments on mice indicate that the method is capable of suppressing the noise and achieving smooth time courses of fluorescent yield. Results of both the simulations and in vivo experiments demonstrate that the Laplacian-type regularization can improve the image quality.

A novel navigation template for fixation of acetabular posterior column fractures with antegrade lag screws: design and application.

PURPOSE: To test whether a novel guide template we designed can facilitate accurate insertion of antegrade lag screws in the fixation of acetabular posterior column fractures. METHODS: We created virtual three-dimensional reconstruction models of the pelvis from CT scan data obtained from 96 adult patients without any bony problems. A virtual cylindrical implant was placed along the longitudinal axis of the acetabular posterior column passing through the ischial tuberosity. The diameter of cylindrical implant was augmented to 6.5 mm, and the direction was adjusted until the optimal screw path was found using the reverse engineering technique. The orifice of this cylinder from the iliac fossa was determined as the entry point for the antegrade lag screw. The anatomical parameters of the screw entry path were measured and saved in .stl format. The guide template was designed according to the acetabular morphology and the measured anatomical parameters before it was put into manufacture of a solid template with the rapid prototyping technique. The feasibility and accuracy of the guide template were tested in cadaveric pelvises. Finally, the guide template was used in real surgery for five patients. Furthermore, the time required for surgery was recorded. RESULTS: Under the guide of this navigation template, antegrade lag screws were successfully placed in the posterior column of the acetabulum in the cadaveric test. And five lag screws were successfully placed in five patients. The mean time of antegrade lag screw insertion required 5.8 (3-10) min. CONCLUSIONS: Antegrade lag screws can be more accurately put into the posterior column of the acetabulum with the help of this navigation template.

Fast reconstruction of fluorophore concentration variation based on the derivation of the diffusion equation.

The information of fluorophore concentration variation (FCV) has the potential for drug development and tumor studies, but the reconstruction of FCV is time-consuming in dynamic fluorescence molecular tomography (DFMT). In this paper, a time-efficient reconstruction method for FCV is presented. The system equation of this method is derived from the derivation of the diffusion equation, and its size does not change with the number of frames. The computational time can be significantly reduced by using this method because the images of different frames are reconstructed separately. Simulations and phantom experiments are performed to validate the performance of the proposed method. The results show that compared with the previous method, the proposed method can obtain better results and consumes less computational time with the same number of iterations. In addition, the time consumption in a single iteration of the proposed method increases much slower with the number of frames.

Image reconstruction for synchronous data acquisition in fluorescence molecular tomography.

The present full-angle, free-space fluorescence molecular tomography (FMT) system uses a step-by-step strategy to acquire measurements, which consumes time for both the rotation of the object and the integration of the charge-coupled device (CCD) camera. Completing the integration during the rotation is a more time-efficient strategy called synchronous data acquisition. However, the positions of sources and detectors in this strategy are not stationary, which is not taken into account in the conventional reconstruction algorithm. In this paper we propose a reconstruction algorithm based on the finite element method (FEM) to overcome this problem. Phantom experiments were carried out to validate the performance of the algorithm. The results show that, compared with the conventional reconstruction algorithm used in the step-by-step data acquisition strategy, the proposed algorithm can reconstruct images with more accurate location data and lower relative errors when used with the synchronous data acquisition strategy.

A method of extracting structural priors from images of micro-CT for fluorescence molecular tomography reconstruction.

The dual-modality systems combined fluorescence molecular tomography (FMT) and micro-computed tomography (micro-CT) can provide molecular and anatomical information of small animals simultaneously. Except for anatomic localization, micro-CT should also offer boundary of different organs as reconstruction priors for FMT, which is more challenging than acquisition of structural information. In this paper, we propose a framework to extract structural priors of a living mouse with micro-CT. The iodinated lipid emulsion contrast agent was adopted to enhance the contrast of the soft tissues of the mouse. Then organs in thorax and abdomen were segmented with different approaches depending on the characteristics of the organs. Bone, lung, heart, liver, spleen, and muscles were separately segmented. And the results were compared with that manually segmented. The Tanimoto coefficient and the relative volume difference of segmented slices were measured to be 91.28 ± 5.78 and 0.27 ± 3.15, respectively. In our simulation study of FMT reconstruction, the errors of measured position and concentration of the fluorophore with priors declined by 89.7% and 79.6% in thorax, as well as 80.8% and 78.3% in abdomen, respectively, compared with the results without priors. The proposed scheme will make FMT reconstruction much more reliable and practical in small animal study.

[Estimation of vegetation water content from Landsat 8 OLI data].

The present paper aims to analyze the capabilities and limitations for retrieving vegetation water content from Landsat8 OLI (Operational Land Imager) sensor-new generation of earth observation program. First, the effect of soil background on canopy reflectance and the sensitive band to vegetation water content were analyzed based on simulated dataset from ProSail model. Then, based on vegetation water indices from Landsat8 OLI and field vegetation water content during June 1 2013 to August 14 2013, the best vegetation water index for estimating vegetation water content was found through comparing 12 different indices. The results show that: (1) red, near infrared and two shortwave infrared bands of OLI sensor are sensitive to the change in vegetation water content, and near infrared band is the most sensitive one; (2) At low vegetation coverage, solar radiation reflected by soil background will reach to spectral sensor and influence the relationship between vegetation water index and vegetation water content, and simulation results from ProSail model also show that soil background reflectance has a significant impact on vegetation canopy reflectance in both wet and dry soil conditions, so the optimized soil adjusted vegetation index (OSAVI) was used in this paper to remove the effect of soil background on vegetation water index and improve its relationship with vegetation water content; (3) for the 12 vegetation water indices, the relationship between MSI2 and vegetation water content is the best with the R-square of 0.948 and the average error of vegetation water content is 0.52 kg · m(-2); (4) it is difficult to estimate vegetation water content from vegetation water indices when vegetation water content is larger than 2 kg · m(-2) due to spectral saturation of these indices.