Differentially Private Adaptive Optimization with Delayed Preconditioners

Privacy noise may negate the benefits of using adaptive optimizers in differentially private model training. Prior works typically address this issue by using auxiliary information (e.g., public data) to boost the effectiveness of adaptive optimization. In this work, we explore techniques to estimate and efficiently adapt to gradient geometry in private adaptive optimization without auxiliary data. Motivated by the observation that adaptive methods can tolerate stale preconditioners, we propose differentially private adaptive training with delayed preconditioners (DP^2), a simple method that constructs delayed but less noisy preconditioners to better realize the benefits of adaptivity. Theoretically, we provide convergence guarantees for our method for both convex and non-convex problems, and analyze trade-offs between delay and privacy noise reduction. Empirically, we explore DP^2 across several real-world datasets, demonstrating that it can improve convergence speed by as much as 4x relative to non-adaptive baselines and match the performance of state-of-the-art optimization methods that require auxiliary data.Comment: Accepted by ICLR 202

6-Deoxyhexoses froml-Rhamnose in the Search for Inducers of the Rhamnose Operon: Synergy of Chemistry and Biotechnology

In the search for alternative non‐metabolizable inducers in the l ‐rhamnose promoter system, the synthesis of fifteen 6‐deoxyhexoses from l ‐rhamnose demonstrates the value of synergy between biotechnology and chemistry. The readily available 2,3‐acetonide of rhamnonolactone allows inversion of configuration at C4 and/or C5 of rhamnose to give 6‐deoxy‐d ‐allose, 6‐deoxy‐d ‐gulose and 6‐deoxy‐l ‐talose. Highly crystalline 3,5‐benzylidene rhamnonolactone gives easy access to l ‐quinovose (6‐deoxy‐l ‐glucose), l ‐olivose and rhamnose analogue with C2 azido, amino and acetamido substituents. Electrophilic fluorination of rhamnal gives a mixture of 2‐deoxy‐2‐fluoro‐l ‐rhamnose and 2‐deoxy‐2‐fluoro‐l ‐quinovose. Biotechnology provides access to 6‐deoxy‐l ‐altrose and 1‐deoxy‐l ‐fructose

Functional consequence of the MET-T1010I polymorphism in breast cancer.

Major breast cancer predisposition genes, only account for approximately 30% of high-risk breast cancer families and only explain 15% of breast cancer familial relative risk. The HGF growth factor receptor MET is potentially functionally altered due to an uncommon germline single nucleotide polymorphism (SNP), MET-T1010I, in many cancer lineages including breast cancer where the MET-T1010I SNP is present in 2% of patients with metastatic breast cancer. Expression of MET-T1010I in the context of mammary epithelium increases colony formation, cell migration and invasion in-vitro and tumor growth and invasion in-vivo. A selective effect of MET-T1010I as compared to wild type MET on cell invasion both in-vitro and in-vivo suggests that the MET-T1010I SNP may alter tumor pathophysiology and should be considered as a potential biomarker when implementing MET targeted clinical trials

Large scale enzyme based xenobiotic identification for exposomics.

Advances in genomics have revealed many of the genetic underpinnings of human disease, but exposomics methods are currently inadequate to obtain a similar level of understanding of environmental contributions to human disease. Exposomics methods are limited by low abundance of xenobiotic metabolites and lack of authentic standards, which precludes identification using solely mass spectrometry-based criteria. Here, we develop and validate a method for enzymatic generation of xenobiotic metabolites for use with high-resolution mass spectrometry (HRMS) for chemical identification. Generated xenobiotic metabolites were used to confirm identities of respective metabolites in mice and human samples based upon accurate mass, retention time and co-occurrence with related xenobiotic metabolites. The results establish a generally applicable enzyme-based identification (EBI) for mass spectrometry identification of xenobiotic metabolites and could complement existing criteria for chemical identification

Determining Thresholds for Three Indices of Autoregulation to Identify the Lower Limit of Autoregulation During Cardiac Surgery.

OBJECTIVES: Monitoring cerebral autoregulation may help identify the lower limit of autoregulation in individual patients. Mean arterial blood pressure below lower limit of autoregulation appears to be a risk factor for postoperative acute kidney injury. Cerebral autoregulation can be monitored in real time using correlation approaches. However, the precise thresholds for different cerebral autoregulation indexes that identify the lower limit of autoregulation are unknown. We identified thresholds for intact autoregulation in patients during cardiopulmonary bypass surgery and examined the relevance of these thresholds to postoperative acute kidney injury. DESIGN: A single-center retrospective analysis. SETTING: Tertiary academic medical center. PATIENTS: Data from 59 patients was used to determine precise cerebral autoregulation thresholds for identification of the lower limit of autoregulation. These thresholds were validated in a larger cohort of 226 patients. METHODS AND MAIN RESULTS: Invasive mean arterial blood pressure, cerebral blood flow velocities, regional cortical oxygen saturation, and total hemoglobin were recorded simultaneously. Three cerebral autoregulation indices were calculated, including mean flow index, cerebral oximetry index, and hemoglobin volume index. Cerebral autoregulation curves for the three indices were plotted, and thresholds for each index were used to generate threshold- and index-specific lower limit of autoregulations. A reference lower limit of autoregulation could be identified in 59 patients by plotting cerebral blood flow velocity against mean arterial blood pressure to generate gold-standard Lassen curves. The lower limit of autoregulations defined at each threshold were compared with the gold-standard lower limit of autoregulation determined from Lassen curves. The results identified the following thresholds: mean flow index (0.45), cerebral oximetry index (0.35), and hemoglobin volume index (0.3). We then calculated the product of magnitude and duration of mean arterial blood pressure less than lower limit of autoregulation in a larger cohort of 226 patients. When using the lower limit of autoregulations identified by the optimal thresholds above, mean arterial blood pressure less than lower limit of autoregulation was greater in patients with acute kidney injury than in those without acute kidney injury. CONCLUSIONS: This study identified thresholds of intact and impaired cerebral autoregulation for three indices and showed that mean arterial blood pressure below lower limit of autoregulation is a risk factor for acute kidney injury after cardiac surgery

GHOSTM: A GPU-Accelerated Homology Search Tool for Metagenomics

A large number of sensitive homology searches are required for mapping DNA sequence fragments to known protein sequences in public and private databases during metagenomic analysis. BLAST is currently used for this purpose, but its calculation speed is insufficient, especially for analyzing the large quantities of sequence data obtained from a next-generation sequencer. However, faster search tools, such as BLAT, do not have sufficient search sensitivity for metagenomic analysis. Thus, a sensitive and efficient homology search tool is in high demand for this type of analysis.We developed a new, highly efficient homology search algorithm suitable for graphics processing unit (GPU) calculations that was implemented as a GPU system that we called GHOSTM. The system first searches for candidate alignment positions for a sequence from the database using pre-calculated indexes and then calculates local alignments around the candidate positions before calculating alignment scores. We implemented both of these processes on GPUs. The system achieved calculation speeds that were 130 and 407 times faster than BLAST with 1 GPU and 4 GPUs, respectively. The system also showed higher search sensitivity and had a calculation speed that was 4 and 15 times faster than BLAT with 1 GPU and 4 GPUs.We developed a GPU-optimized algorithm to perform sensitive sequence homology searches and implemented the system as GHOSTM. Currently, sequencing technology continues to improve, and sequencers are increasingly producing larger and larger quantities of data. This explosion of sequence data makes computational analysis with contemporary tools more difficult. We developed GHOSTM, which is a cost-efficient tool, and offer this tool as a potential solution to this problem

Synthetic Chemical Inducers and Genetic Decoupling Enable Orthogonal Control of the rhaBAD Promoter

External control of gene expression is crucial in synthetic biology and biotechnology research and applications, and is commonly achieved using inducible promoter systems. The E. coli rhamnose-inducible rhaBAD promoter has properties superior to more commonly used inducible expression systems, but is marred by transient expression caused by degradation of the native inducer, l-rhamnose. To address this problem, 35 analogues of l-rhamnose were screened for induction of the rhaBAD promoter, but no strong inducers were identified. In the native configuration, an inducer must bind and activate two transcriptional activators, RhaR and RhaS. Therefore, the expression system was reconfigured to decouple the rhaBAD promoter from the native rhaSR regulatory cascade so that candidate inducers need only activate the terminal transcription factor RhaS. Rescreening the 35 compounds using the modified rhaBAD expression system revealed several promising inducers. These were characterized further to determine the strength, kinetics, and concentration-dependence of induction; whether the inducer was used as a carbon source by E. coli; and the modality (distribution) of induction among populations of cells. l-Mannose was found to be the most useful orthogonal inducer, providing an even greater range of induction than the native inducer l-rhamnose, and crucially, allowing sustained induction instead of transient induction. These findings address the key limitation of the rhaBAD expression system and suggest it may now be the most suitable system for many applications

Imaging Trans-Cellular Neurexin-Neuroligin Interactions by Enzymatic Probe Ligation

Neurexin and neuroligin are transmembrane adhesion proteins that play an important role in organizing the neuronal synaptic cleft. Our lab previously reported a method for imaging the trans-synaptic binding of neurexin and neuroligin called BLINC (Biotin Labeling of INtercellular Contacts). In BLINC, biotin ligase (BirA) is fused to one protein while its 15-amino acid acceptor peptide substrate (AP) is fused to the binding partner. When the two fusion proteins interact across cellular junctions, BirA catalyzes the site-specific biotinylation of AP, which can be read out by staining with streptavidin-fluorophore conjugates. Here, we report that BLINC in neurons cannot be reproduced using the reporter constructs and labeling protocol previously described. We uncover the technical reasons for the lack of reproducibilty and then re-design the BLINC reporters and labeling protocol to achieve neurexin-neuroligin BLINC imaging in neuron cultures. In addition, we introduce a new method, based on lipoic acid ligase instead of biotin ligase, to image trans-cellular neurexin-neuroligin interactions in human embryonic kidney cells and in neuron cultures. This method, called ID-PRIME for Interaction-Dependent PRobe Incorporation Mediated by Enzymes, is more robust than BLINC due to higher surface expression of lipoic acid ligase fusion constructs, gives stronger and more localized labeling, and is more versatile than BLINC in terms of signal readout. ID-PRIME expands the toolkit of methods available to study trans-cellular protein-protein interactions in living systems.National Institutes of Health (U.S.) (DP1 OD003961

Quantum Dot Targeting with Lipoic Acid Ligase and HaloTag for Single-Molecule Imaging on Living Cells

We present a methodology for targeting quantum dots to specific proteins on living cells in two steps. In the first step, Escherichia coli lipoic acid ligase (LplA) site-specifically attaches 10-bromodecanoic acid onto a 13 amino acid recognition sequence that is genetically fused to a protein of interest. In the second step, quantum dots derivatized with HaloTag, a modified haloalkane dehalogenase, react with the ligated bromodecanoic acid to form a covalent adduct. We found this targeting method to be specific, fast, and fully orthogonal to a previously reported and analogous quantum dot targeting method using E. coli biotin ligase and streptavidin. We used these two methods in combination for two-color quantum dot visualization of different proteins expressed on the same cell or on neighboring cells. Both methods were also used to track single molecules of neurexin, a synaptic adhesion protein, to measure its lateral diffusion in the presence of neuroligin, its trans-synaptic adhesion partner.National Institutes of Health (U.S.) (R01 GM072670)Camille & Henry Dreyfus FoundationMassachusetts Institute of Technology. Computational and Systems Biology Program. MIT-Merck Postdoctoral Fellowshi

Integrative analysis of RUNX1 downstream pathways and target genes

Background: The RUNX1 transcription factor gene is frequently mutated in sporadic myeloid and lymphoid leukemia through translocation, point mutation or amplification. It is also responsible for a familial platelet disorder with predisposition to acute myeloid leukemia (FPD-AML). The disruption of the largely unknown biological pathways controlled by RUNX1 is likely to be responsible for the development of leukemia. We have used multiple microarray platforms and bioinformatic techniques to help identify these biological pathways to aid in the understanding of why RUNX1 mutations lead to leukemia. Results: Here we report genes regulated either directly or indirectly by RUNX1 based on the study of gene expression profiles generated from 3 different human and mouse platforms. The platforms used were global gene expression profiling of: 1) cell lines with RUNX1 mutations from FPD-AML patients, 2) over-expression of RUNX1 and CBF[Beta], and 3) Runx1 knockout mouse embryos using either cDNA or Affymetrix microarrays. We observe that our datasets (lists of differentially expressed genes) significantly correlate with published microarray data from sporadic AML patients with mutations in either RUNX1 or its cofactor, CBF[Beta]. A number of biological processes were identified among the differentially expressed genes and functional assays suggest that heterozygous RUNX1 point mutations in patients with FPD-AML impair cell proliferation, microtubule dynamics and possibly genetic stability. In addition, analysis of the regulatory regions of the differentially expressed genes has for the first time systematically identified numerous potential novel RUNX1 target genes. Conclusion: This work is the first large-scale study attempting to identify the genetic networks regulated by RUNX1, a master regulator in the development of the hematopoietic system and leukemia. The biological pathways and target genes controlled by RUNX1 will have considerable importance in disease progression in both familial and sporadic leukemia as well as therapeutic implications