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Generalizable and Non-genetic Approach to Create Metabolically-active-but-non-replicating Bacteria

Researchers at the University of California, Davis have developed a method to stop bacterial growth while maintaining desirable metabolic functions for therapeutic and biotechnological applications.

Nuclear Delivery and Transcriptional Repression with a Cell-penetrant MeCP2

Methyl-CpG-binding-protein 2 (MeCP2) is a nuclear protein expressed in all cell types, especially neurons. Mutations in the MECP2 gene cause Rett syndrome (RTT), an incurable neurological disorder that disproportionately affects young girls. Strategies to restore MeCP2 expression phenotypically reverse RTT-like symptoms in male and female MeCP2-deficient mice, suggesting that direct nuclear delivery of functional MeCP2 could restore MeCP2 activity.The inventors have discovered that ZF-tMeCP2, a conjugate of MeCP2(aa13-71, 313-484) and the cell-permeant mini-protein ZF5.3, binds DNA in a methylation-dependent manner and reaches the nucleus of model cell lines intact at concentrations above 700 nM. When delivered to live cells, ZF-tMeCP2 engages the NCoR/SMRT co-repressor complex and selectively represses transcription from methylated promoters. Efficient nuclear delivery of ZF-tMeCP2 relies on a unique endosomal escape portal provided by HOPS-dependent endosomal fusion.In a comparative evaluation, the inventors observed the Tat conjugate of MeCP2 (Tat-tMeCP2) (1) degrades within the nucleus, (2) is not selective for methylated promoters, and (3) traffics in a HOPS-independent manner. These results support the feasibility of a HOPS-dependent portal for delivering functional macromolecules to the cell interior using the cell-penetrant mini-protein ZF5.3. Such a strategy could broaden the impact of multiple families of protein-derived therapeutics.

Membrane-Associated Accessory Protein Variants Confer Increased AAV Production

The inventors have developed an engineering approach to identify novel and nonobvious membrane-associated accessory protein (MAAP) sequence variants that confer increased Adeno-associated virus (AAV) secretion during packaging. The technique is based upon the iterative process of sequence diversification and selection of functional gene variants known as directed evolution. First, the inventors generated a library of more than 1E6 MAAP variants. The variants were subjected to five rounds of packaging into an AAV2 capsid for which MAAP expression was inactivated without altering the viral protein VP1 open reading frame (ORF) (AAV2-MAAP-null). Among each iterative packaging round, the inventors observed a progressive increase in both the overall titer and ratio of secreted vector genomes conferred by the bulk selected MAAP library population. Next-generation sequencing uncovered common mutational features that were enriched up to over 10,000-fold on the amino acid level. Individual MAAP variants were isolated and systematically tested for effect on recombinant AAV2-MAAP-null packaging in HEK293 cells. The inventors predict that this work may be applicable to increasing per-cell AAV output in industrial settings, potentially reducing global costs and increasing functional vector recovery in downstream manufacturing processes.BACKGROUNDParvoviruses are small, single-stranded DNA viruses that are ubiquitously found in many animal species. AAV is a prototypic dependoparvovirus whose replication cycle requires the function of helper genes from larger co-infected viruses such as Adenoviruses or Herpesviruses. The natural genome of AAV contains ~4.7 kb of ssDNA that encodes up to ten known proteins in a highly overlapped fashion. The rep gene encodes four protein products named based on their molecular weight: Rep72 and Rep68 facilitate genomic replication, whereas Rep52, and Rep40 play essential roles in loading nascent ssDNA genomes into assembled capsids. Downstream of rep lies the cap gene, which encodes three known protein products off of overlapping reading frames: VP1, VP2, and VP3 are structural proteins that assemble to form the capsid, the assembly activating protein (AAP) targets VP proteins to the nucleus and is involved in capsid assembly. The most recently discovered AAV-encoded gene is the membrane-associated accessory protein (MAAP). MAAP is encoded by an alternative ORF in the AAV cap gene that is found in all presently reported natural serotypes. Gene delivery by recombinant AAV (rAAV) have shown significant success in both research and clinical gene therapy applications. In the rAAV system, Rep and Cap are removed from between AAV’s 5’ and 3’ inverted terminal repeats (ITRs) and provided in trans. Instead, a transgene of interest is inserted between the ITRs and subsequently packaged into the nascent AAV capsids. However, manufacturing quantities of good manufacturing practice (GMP)-grade rAAVs necessary to achieve current and projected dosing requirements–particularly in a clinical context–presents a significant hurdle to expanding rAAV-based gene therapies. Recently, evidence has emerged supporting a functional role of MAAP in AAV egress. This led to the hypothesis that MAAP could be engineered to facilitate increased levels of secreted AAV produced from HEK293 cells. 

Compositions and Methods for Modification of Cells

New chemistries are emerging for the direct attachment of complex molecules to cell surfaces. Chemistries that modify cells must perform under a narrow set of conditions in order to maintain cell viability. They must proceed in buffered aqueous media at the optimal physiological pH—typically pH 7.4—and within a temperature range of 4 – 37 ºC. Furthermore, these reactions must have sufficiently rapid kinetics to achieve high conversion even when confronted with the limits of surface diffusion characteristics. Due to these requirements, few chemistries exist that can attach molecules and proteins to live cells.  There is a need for improved methods of attaching proteins to living cells.   UC researchers have developed a convenient enzymatic strategy for the modification of cell surfaces for targeted immunotherapy applications.  

RNA-Guided Fusion Proteins for Targeted Diversification of Cytoplasmic DNA

The inventors have developed a method of mutagenizing user-defined regions of cytoplasmic DNA using a single guide RNA (sgRNA) or combinations of sgRNAs and a highly engineered fusion polypeptide comprising: a nuclear export sequence (NES)-containing, engineered nuclear localization sequence (NLS)-lacking, enzymatically active, RNA-guided endonuclease that introduces a single-stranded break in cytoplasmic DNA, and an error-prone DNA polymerase. This novel technology encompasses and provides evidence for the use of RNA-guided nucleases with relaxed PAM requirements, which are particularly useful for AT-rich targets such as the vaccinia virus genome. The inventors show that the truncation of up to several base pairs from the PAM-distal template binding region of the sgRNAs significantly increases the functional activity and specificity of the targeted mutagenesis complex. Moreover, the invention describes specific methods for the use of this technology to edit cytoplasmically replicating viruses with large DNA genomes, using poxviruses as a model system. The novel editing platform and methods selectively and continuously accelerate diversification of user-defined sites in the vaccinia genome during infection, while retaining most library members, due to significantly lowering deleterious off-target mutations. BACKGROUND Nucleocytoplasmic large DNA viruses (NCLDVs) are a group of viruses that harbor large (150 kbp - 1.2 mbp) double-stranded DNA genomes and replicate in the cytoplasm of eukaryotic cells. An example of an NCLDV that has historically been among the most prominent tools in human health is vaccinia, a poxvirus. Hundreds of millions of humans have been intentionally inoculated with vaccinia as part of a global effort to eliminate smallpox, which was declared eradicated in 1980.Vaccinia and some other poxviruses remain highly scientifically relevant in the post-eradication world. They are useful as vaccines against deadly poxvirus outbreaks that could potentially arise from natural spillover, bioterrorism, or biowarfare, as well as due to their therapeutic promise as oncolytic agents to selectively deliver anti-cancer transgenes and recruit adaptive immunity while leaving healthy cells unharmed. Directed evolution is a powerful engineering technique for evolving new phenotypes that are beneficial for biotechnological applications but for which there may have never been a selective pressure to evolve in nature. Both natural and directed evolution depend upon generation of genetic diversity, followed by a selective pressure. While natural evolution generates genetic diversity randomly and throughout the entirety of the genome, directed evolution ideally focuses mutations within specific genomic windows connected to the phenotype that one wishes to engineer. However, there is a need in the art for compositions and methods for mutagenizing a target DNA in the cytoplasm of mammalian cells. NCLDVs, which either partially or entirely express their own replicative and translational machinery independent of the nucleus, are difficult, and in many cases impossible, to produce from plasmid DNA in cells. Thus, NCLDVs are not amenable to standard in vitro molecular diversification strategies.  

(SD2021-335) Personalized Machine Learning of Depressed Mood using Wearables (software)

Depression is a multifaceted illness with genetic, behavioral, lifestyle, and interpersonal risk factors that may express as overlapping symptoms, which in turn leads to huge interindividual variability in clinical response to the same treatments or behavioral recommendations.In the era of digital medicine and precision therapeutics, new personalized treatment approaches are warranted for depression.

Systems and Methods for Scaling Electromagnetic Apertures, Single Mode Lasers, and Open Wave Systems

The inventors have developed a scalable laser aperture that emits light perpendicular to the surface. The aperture can, in principal, scale to arbitrarily large sizes, offering a universal architecture for systems in need of small, intermediate, or high power. The technology is based on photonic crystal apertures, nanostructured apertures that exhibit a quasi-linear dispersion at the center of the Brillouin zone together with a mode-dependent loss controlled by the cavity boundaries, modes, and crystal truncation. Open Dirac cavities protect the fundamental mode and couple higher order modes to lossy bands of the photonic structure. The technology was developed with an open-Dirac electromagnetic aperture, known as a Berkeley Surface Emitting Laser (BKSEL).  The inventors demonstrate a subtle cavity-mode-dependent scaling of losses. For cavities with a quadratic dispersion, detuned from the Dirac singularity, the complex frequencies converge towards each other based on cavity size. While the convergence of the real parts of cavity modes towards each other is delayed, going quickly to zero, the normalized complex free-spectral range converge towards a constant solely governed by the loss rate of Bloch bands. The inventors show that this unique scaling of the complex frequency of cavity modes in open-Dirac electromagnetic apertures guarantees single-mode operation of large cavities. The technology demonstrates scaled up single-mode lasing, and confirmed from far-field measurements. By eliminating limits on electromagnetic aperture size, the technology will enable groundbreaking applications for devices of all sizes, operating at any power level. BACKGROUND Single aperture cavities are bounded by higher order transverse modes, fundamentally limiting the power emitted by single-mode lasers, as well as the brightness of quantum light sources. Electromagnetic apertures support cavity modes that rapidly become arbitrarily close with the size of the aperture. The free-spectral range of existing electromagnetic apertures goes to zero when the size of the aperture increases. As a result, scale-invariant apertures or lasers has remained elusive until now.  Surface-emitting lasers have advantages in scalability over commercially widespread vertical-cavity surface-emitting lasers (VCSELs). When a photonic crystal is truncated to a finite cavity, the continuous bands break up into discrete cavity modes. These higher order modes compete with the fundamental lasing mode and the device becomes more susceptible to multimode lasing response as the cavity size increases. 

Engineering Cas12a Genome Editors with Minimized Trans-Activity

The inventors engineered a set of LbCas12a mutants through rational design and directed evolution. The engineered mutants can function as efficient genome editors with minimized trans-activity.

(SD2020-421) Virtual Electrodes for Imaging of Cortex-Wide Brain Activity: Decoding of cortex-wide brain activity from local recordings of neural potentials

As an important tool for electrophysiological recordings, neural electrodes implanted on the brain surface have been instrumental in basic neuroscience research to study large-scale neural dynamics in various cognitive processes, such as sensorimotor processing as well as learning and memory. In clinical settings, neural recordings have been adopted as a standard tool to monitor the brain activity in epilepsy patients before surgery for detection and localization of epileptogenic zones initiating seizures and functional cortical mapping. Neural activity recorded from the brain surface exhibits rich information content about the collective neural activities reflecting the cognitive states and brain functions. For the interpretation of surface potentials in terms of their neural correlates, most research has focused on local neural activities.   From basic neuroscience research to clinical treatments and neural engineering, electrocorticography (ECoG) has been widely used to record surface potentials to evaluate brain function and develop neuroprosthetic devices. However, the requirement of invasive surgeries for implanting ECoG arrays significantly limits the coverage of different cortical regions, preventing simultaneous recordings from spatially distributed cortical networks. However, this rich information content of surface potentials encoded for the large-scale cortical activity remains unexploited and little is known on how local surface potentials are correlated with the spontaneous neural activities of distributed large-scale cortical networks. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri",sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

Deep Learning-Based Approach to Accelerate T cell Receptor Design

Researchers at the University of California, Davis have developed a deep learning simulation model to predict mutated T-cell receptor affinity and avidity for immunotherapy applications.

Reinforcement Learning with Real-time Docking of 3D Structures for SARS-COV-2

The inventors propose a novel framework generating new molecules that potentially inhibit the Mpro protein, the main protease of SARS-COV-2. The technology combines deep reinforcement learning (RL) with real-time molecular docking on the 3d structure of Mpro using AutoDock Vina, an open-source program for doing molecular docking. A second second docking software, Glide, was used to validate the generated molecules. The AutoDock and Glide docking softwares showed consensus on 41 molecules as potential potent Mpro inhibitors that were sufficiently easy to synthesize. The inventors show that this method samples the drug chemical space efficiently, covering a much broader space than molecules submitted to the COVID moonshot project, and the molecules have the correct shape and non-bonded interactions to fit into the binding pocket. Moreover, this approach only relies on the structure of the target protein, which means it can be easily adapted for future development of other inhibitors.

Programmable System that Mixes Large Numbers of Small Volume, High-Viscosity, Fluid Samples Simultaneously

Researchers at the University of California, Davis have developed a programmable machine that shakes and repeatedly inverts large numbers of small containers - such as vials and flasks – in order to mix high-viscosity fluids.

Aluminum Microchips for Biosensing and Pathogen Identification

Prof. Quan Cheng and colleagues from the University of California, Riverside have developed aluminum (Al) microchips for highly sensitive SPR detection of bioanalytical targets. This technology allows for determination of binding kinetics of drug targets and disease marker detection. In addition to applications for SPR, these Al microchips enable other surface-based techniques such as enhanced Raman spectroscopy and MALDI-MS for direct pathogen identification. Compared to traditional gold substrates, Al has a broad range of advantages. It is more plasmonically active, leading to high optical sensitivity, and it is chemically flexible for design of various analytical platforms. Al also has several manufacturing benefits that make it commercially appealing when compared to gold, such as higher abundance, lower cost, and simple integration into existing manufacturing processes such as CMOS. Fig 1: (Top) Fabrication of aluminum microchips. (Bottom) Aluminum demonstrates a high theoretical and practical plasmonic activity correlating to a higher detection sensitivity for biological targets.  

Plasmonic Gold Microchips for Swift Microbial Identification with MALDI-MS

Prof. Quan Cheng and colleagues from the University of California, Riverside have developed a gold microchip consisting of a nanoscale film fabricated on a gold substrate for highly effective, matrix-free laser desorption ionization mass spectrometry (LDI-MS) analysis of lipids. This technology allows for effective analysis of low mass metabolites without the need for time consuming extraction methods. The microchip also enhances fluorescent signal through metal enhanced fluorescence (MEF) allowing single cells to be located easily and improves ionization of lipids. Fig 1: Gold microchips enable localization of cells with MEF and efficient ionization of lipid species. The lipid fingerprint can then be used to trace changes caused by toxicants or identify microbial species present.  

Stable N-acetylated analogs of Sialic Acids and Sialosides

Researchers at the University of California, Davis have constructed a library of glycans containing N-acetyl sialic acids to mimic those containing naturally occurring O-acetyl sialic acids.

2-D Polymer-Based Device for Serial X-Ray Crystallography

Researchers at the University of California, Davis have developed a single-use chip for the identification of protein crystals using X-ray based instruments.

One-Pot Multienzyme Synthesis of Sialidase Reagents, Probes and Inhibitors

Researchers at the University of California, Davis, have developed an environmentally friendly one-pot multienzyme (OPME) method for synthesizing sialidase reagents, probes, and inhibitors.

Nanopore Sensor to Characterize Nano and Microscale Particles and Cells

Researchers at the University of California, Riverside can discriminate between mixed populations of cells and particles in solution using pressure to displace objects across a nanopore multiple times.  Ionic current flow through the nanopore indicates the pressure required to translocate the object in the pore, which correlates to the object’s mass and volume.  Key to these results is that a nanopore sensor allows pressure oscillations to capture and release repeatedly the same object to learn about its inertia and morphology.  Such data can provide details about the size and shape of analytes, their morphologies and structural constraints, or even pathological conditions of living cells. Fig. 1 Nanopore sensing of differently sized cells in a mixed bacterial culture.  

Novel Tunable Hydrogel for Biomedical Applications

Prof. Huinan Liu’s lab at the University of California, Riverside has developed a novel tunable hydrogel that achieves tunable crosslinking, reversible phase transition, and may be used as a 3DP scaffold. This new hydrogel utilizes dynamic coordination of its innate carboxylic groups and metal ions. Adding methylacrylate or other functional groups is not required for this technology and the resulting hydrogel is less toxic. Since the functionalization of this hydrogel is not required, it is less process-intensive and results in a more cost-effective hydrogel.  In addition, the UV curing is no longer needed since methylacrylate is no longer utilized to crosslink the hydrogel.   Fig 1: Optical micrographs of top view and cross-section of HyA hydrogels printed using cold-stage method and direct writing method. Hydrogels printed using direct writing method showed better structural integrity and stability.

Protein Inhibitor of Type VI-B CRISPR-Cas System

The inventors have discovered the first protein inhibitor of the type VI-B CRISPR-Cas system. By controlling this CRISPR system, one could possibly ameliorate the toxicity and off-target cleavage activity observed with the use of the type VI CRISPR system. Moreover, these proteins can also serve as an antidote for instances where the use of CRISPR-Cas technology poses a safety risk. Additionally, this technology can also be used for engineering genetic circuits in mammalian cells. This finding is of potential importance to many companies in the CRISPR space. 

Automated Tip Conditioning ML-Based Software For Scanning Tunneling Spectroscopy

Scanning tunneling microscopy (STM) techniques and associated spectroscopic (STS) methods, such as dI/dV point spectroscopy, have been widely used to measure electronic structures and local density of states of molecules and materials with unprecedented spatial and energy resolutions. However, the quality of dI/dV spectra highly depends on the shape of the probe tips, and atomically sharp tips with well-defined apex structures are required for obtaining reliable spectra. In most cases, STS measurements are performed in ultra-high vacuum  and low temperature (4 K) to minimize disturbances. Advance tip preparation and constant in situ tip conditioning are required before and during the characterization of target molecules and materials. A common way to prepare STM tips is to repetitively poke them on known and bare substrates (i.e. coinage metals or silicon) to remove contaminations and to potentially coat the tip with substrate atoms. The standard dI/dV spectra of the substrate is then used as a reference to determine whether the tip is available for further experiments. However, tip geometry changes during the poking process are unpredictable, and consequently tip conditioning is typically slow and needs to be constantly monitored. Therefore, it restricts the speed of high-quality STM spectroscopic studies. In order to make efficient use of instrument idle time and minimize the research time wasted on tip conditioning, UC Berkeley researchers developed software based on Python and machine learning that can automate the time-consuming tip conditioning processes. The program is designed to do tip conditioning on Au(111) surfaces that are clean or with low molecular coverage with little human intervention. By just one click, the program is capable of continued poking until the tip can generate near-publication quality spectroscopic data on gold surfaces. It can control the operation of a Scienta Omicron STM and automatically analyze the collected topographic images to find bare Au areas that are large enough for tip conditioning. It will then collect dI/dV spectra at selected positions and use machine learning models to determine their quality compared to standard dI/dV spectra for Au20 and determine if the tip is good enough for further STS measurements. If the tip condition is not ideal, the program will control the STM to poke at the identified positions until the machine learning model predicts the tip to be in good condition.

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