Residue-Level Characterization of Antibody Binding Epitopes Using Carbene Chemical Footprinting.

Characterization of antibody binding epitopes is an important factor in therapeutic drug discovery, as the binding site determines and drives antibody pharmacology and pharmacokinetics. Here, we present a novel application of carbene chemical footprinting with mass spectrometry for identification of antibody binding epitopes at the single-residue level. Two different photoactivated diazirine reagents provide complementary labeling information allowing structural refinement of the antibody binding interface. We applied this technique to map the epitopes of multiple MICA and CTLA-4 antibodies and validated the findings with X-ray crystallography and yeast surface display epitope mapping. The characterized epitopes were used to understand biolayer interferometry-derived competitive binding results at the structural level. We show that carbene footprinting provides fast and high-resolution epitope information critical in the antibody selection process and enables mechanistic understanding of function to accelerate the drug discovery process.

Impact of Drug Conjugation on Thermal and Metabolic Stabilities of Aglycosylated and N-Glycosylated Antibodies.

N-linked glycosylation is one of the most common and complex posttranslational modifications that govern the biological functions and physicochemical properties of therapeutic antibodies. We evaluated thermal and metabolic stabilities of antibody-drug conjugates (ADCs) with payloads attached to the C'E loop in the immunoglobulin G (IgG) Fc CH2 domain, comparing the glycosylated and aglycosylated Fc ADC variants. Our study revealed that introduction of small-molecule drugs into an aglycosylated antibody can compensate for thermal destabilization originating from structural distortions caused by elimination of N-linked glycans. Depending on the conjugation site, glycans had both positive and negative effects on plasma stability of ADCs. The findings highlight the importance of consideration for selection of conjugation site to achieve desirable physicochemical properties and plasma stability.

Atom Interferometry with Floquet Atom Optics.

Floquet engineering offers a compelling approach for designing the time evolution of periodically driven systems. We implement a periodic atom-light coupling to realize Floquet atom optics on the strontium ^{1}S_{0}-^{3}P_{1} transition. These atom optics reach pulse efficiencies above 99.4% over a wide range of frequency offsets between light and atomic resonance, even under strong driving where this detuning is on the order of the Rabi frequency. Moreover, we use Floquet atom optics to compensate for differential Doppler shifts in large momentum transfer atom interferometers and achieve state-of-the-art momentum separation in excess of 400 ℏk. This technique can be applied to any two-level system at arbitrary coupling strength, with broad application in coherent quantum control.

High-Throughput Platform to Identify Antibody Conjugation Sites from Antibody-Drug Conjugate Libraries.

Antibody-drug conjugates (ADCs) are a therapeutic modality that traditionally enable the targeted delivery of highly potent cytotoxic agents to specific cells such as tumor cells. More recently, antibodies have been used to deliver molecules such as antibiotics, antigens, and adjuvants to bacteria or specific immune cell subsets. Site-directed mutagenesis of proteins permits more precise control over the site and stoichiometry of their conjugation, giving rise to homogeneous chemically defined ADCs. Identification of favorable sites for conjugation in antibodies is essential as reaction efficiency and product stability are influenced by the tertiary structure of immunoglobulin G (IgG). Current methods to evaluate potential conjugation sites are time-consuming and labor intensive, involving multistep processes for individually produced reactions. Here, we describe a highly efficient method for identification of conjugatable genetic variants by analyzing pooled ADC libraries using mass spectrometry. This approach provides a versatile platform to rapidly uncover new conjugation sites for site-specific ADCs.

Large Momentum Transfer Clock Atom Interferometry on the 689 nm Intercombination Line of Strontium.

We report the first realization of large momentum transfer (LMT) clock atom interferometry. Using single-photon interactions on the strontium ^{1}S_{0}-^{3}P_{1} transition, we demonstrate Mach-Zehnder interferometers with state-of-the-art momentum separation of up to 141 ℏk and gradiometers of up to 81 ℏk. Moreover, we circumvent excited state decay limitations and extend the gradiometer duration to 50 times the excited state lifetime. Because of the broad velocity acceptance of the interferometry pulses, all experiments are performed with laser-cooled atoms at a temperature of 3 µK. This work has applications in high-precision inertial sensing and paves the way for LMT-enhanced clock atom interferometry on even narrower transitions, a key ingredient in proposals for gravitational wave detection and dark matter searches.

Effective Inertial Frame in an Atom Interferometric Test of the Equivalence Principle.

In an ideal test of the equivalence principle, the test masses fall in a common inertial frame. A real experiment is affected by gravity gradients, which introduce systematic errors by coupling to initial kinematic differences between the test masses. Here we demonstrate a method that reduces the sensitivity of a dual-species atom interferometer to initial kinematics by using a frequency shift of the mirror pulse to create an effective inertial frame for both atomic species. Using this method, we suppress the gravity-gradient-induced dependence of the differential phase on initial kinematic differences by 2 orders of magnitude and precisely measure these differences. We realize a relative precision of Δg/g≈6×10^{-11} per shot, which improves on the best previous result for a dual-species atom interferometer by more than 3 orders of magnitude. By reducing gravity gradient systematic errors to one part in 10^{13}, these results pave the way for an atomic test of the equivalence principle at an accuracy comparable with state-of-the-art classical tests.

Phase Shift in an Atom Interferometer due to Spacetime Curvature across its Wave Function.

Spacetime curvature induces tidal forces on the wave function of a single quantum system. Using a dual light-pulse atom interferometer, we measure a phase shift associated with such tidal forces. The macroscopic spatial superposition state in each interferometer (extending over 16 cm) acts as a nonlocal probe of the spacetime manifold. Additionally, we utilize the dual atom interferometer as a gradiometer for precise gravitational measurements.

Matter wave lensing to picokelvin temperatures.

Using a matter wave lens and a long time of flight, we cool an ensemble of ^{87}Rb atoms in two dimensions to an effective temperature of less than 50_{-30}^{+50} pK. A short pulse of red-detuned light generates an optical dipole force that collimates the ensemble. We also report a three-dimensional magnetic lens that substantially reduces the chemical potential of evaporatively cooled ensembles with a high atom number. By observing such low temperatures, we set limits on proposed modifications to quantum mechanics in the macroscopic regime. These cooling techniques yield bright, collimated sources for precision atom interferometry.

New method for gravitational wave detection with atomic sensors.

Laser frequency noise is a dominant noise background for the detection of gravitational waves using long-baseline optical interferometry. Amelioration of this noise requires near simultaneous strain measurements on more than one interferometer baseline, necessitating, for example, more than two satellites for a space-based detector or two interferometer arms for a ground-based detector. We describe a new detection strategy based on recent advances in optical atomic clocks and atom interferometry which can operate at long baselines and which is immune to laser frequency noise. Laser frequency noise is suppressed because the signal arises strictly from the light propagation time between two ensembles of atoms. This new class of sensor allows sensitive gravitational wave detection with only a single baseline. This approach also has practical applications in, for example, the development of ultrasensitive gravimeters and gravity gradiometers.

Multiaxis inertial sensing with long-time point source atom interferometry.

We show that light-pulse atom interferometry with atomic point sources and spatially resolved detection enables multiaxis (two rotation, one acceleration) precision inertial sensing at long interrogation times. Using this method, we demonstrate a light-pulse atom interferometer for 87Rb with 1.4 cm peak wave packet separation and a duration of 2T=2.3 s. The inferred acceleration sensitivity of each shot is 6.7×10(-12)g, which improves on previous limits by more than 2 orders of magnitude. We also measure Earth's rotation rate with a precision of 200 nrad/s.

Enhanced atom interferometer readout through the application of phase shear.

We present a method for determining the phase and contrast of a single shot of an atom interferometer. The application of a phase shear across the atom ensemble yields a spatially varying fringe pattern at each output port, which can be imaged directly. This method is broadly relevant to atom-interferometric precision measurement, as we demonstrate in a 10 m 87Rb atomic fountain by implementing an atom-interferometric gyrocompass with 10 mdeg precision.

Generation of 43 W of quasi-continuous 780 nm laser light via high-efficiency, single-pass frequency doubling in periodically poled lithium niobate crystals.

We demonstrate high-efficiency frequency doubling of the combined output of two 1560 nm 30 W fiber amplifiers via single pass through periodically poled lithium niobate (PPLN) crystals. The temporal profile of the 780 nm output is controlled by adjusting the relative phase between the seeds of the amplifiers. We obtain a peak power of 34 W of 780 nm light by passing the combined output through one PPLN crystal, and a peak power of 43 W by passing through two cascading PPLN crystals. This source provides high optical power, excellent beam quality and spectral purity, and agile frequency and amplitude control in a simple and compact setup, which is ideal for applications such as atom optics using Rb atoms.

Preclinical Characterization of Relatlimab, a Human LAG-3-Blocking Antibody, Alone or in Combination with Nivolumab.

Novel therapeutic approaches combining immune-checkpoint inhibitors are needed to improve clinical outcomes for patients with cancer. Lymphocyte-activation gene 3 (LAG-3) is an immune-checkpoint molecule that inhibits T-cell activity and antitumor immune responses, acting through an independent mechanism from that of programmed death-1 (PD-1) and cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4). Here, we describe the development and preclinical characterization of relatlimab, a human antibody that binds to human LAG-3 with high affinity and specificity to block the interaction of LAG-3 with the ligands MHC II and fibrinogen-like protein-1, and to reverse LAG-3-mediated inhibition of T-cell function in vitro. Consistent with previous reports, in mouse models, the combined blockade of LAG-3 and PD-1 with surrogate antibodies resulted in enhanced antitumor activity greater than the individual blockade of either receptor. In toxicity studies in cynomolgus monkeys, relatlimab was generally well tolerated when combined with nivolumab. These results are consistent with findings from the RELATIVITY-047 phase II/III trial showing that relatlimab combined with nivolumab is a well-tolerated regimen that demonstrates superior progression-free survival compared with nivolumab monotherapy in patients with unresectable or metastatic melanoma.

A proteomics platform combining depletion, multi-lectin affinity chromatography (M-LAC), and isoelectric focusing to study the breast cancer proteome.

The discovery of breast cancer associated plasma/serum biomarkers is important for early diagnosis, disease mechanism elucidation, and determination of treatment strategy for the disease. In this study of serum samples, a multidimensional fractionation platform combined with mass spectrometric analysis were used to achieve the identification of medium to lower abundance proteins, as well as to simultaneously detect glycan and abundance changes. Immuno-affinity depletion and multi-lectin chromatography (M-LAC) were integrated into an automated HPLC platform to remove high abundance protein and fractionate glycoproteins. The collected glycoproteomes were then subjected to isoelectric focusing (IEF) separation by a digital ProteomeChip (dPC), followed by in-gel digestion and LC-MS analysis using an Orbitrap mass spectrometer. As a result, the total number of identified proteins increased significantly when the IEF fractionation step was included as part of the platform. Relevant proteins with biological and disease significance were observed and the dynamic range of the serum proteome measurement was extended. In addition, potential glycan changes were indicated by comparing proteins in control and cancer samples in terms of their affinity to the multi-lectin column (M-LAC) and the pI profiles in IEF separation. In conclusion, a proteomics platform including high abundance protein depletion, lectin affinity fractionation, IEF separation, and LC-MS analysis has been applied to discover breast cancer-associated proteins. The following candidates, thrombospondin-1 and 5, alpha-1B-glycoprotein, serum amyloid P-component, and tenascin-X, were selected as promising examples of the use of this platform. They show potential abundance and glycan changes and will be further investigated in future studies.

Antibody blockade of CD96 by distinct molecular mechanisms.

The molecular interactions of mouse CD96 to CD155 ligand and to two surrogate antibodies have been investigated. Biophysical and structural studies demonstrate that CD96 forms a homodimer but assembles as 1:1 heterodimeric complexes with CD155 or with one of the surrogate antibodies, which compete for the same binding interface. In comparison, the other surrogate antibody binds across the mouse CD96 dimer and recognizes a quaternary epitope spanning both protomers to block exposure of the ligand-binding site. This study reveals different blocking mechanisms and modalities of these two antibodies and may provide insight into the functional effects of antibodies against CD96.

Design and characterization of mouse IgG1 and IgG2a bispecific antibodies for use in syngeneic models.

The development of antibody therapeutics relies on animal models that accurately recapitulate disease biology. Syngeneic mouse models are increasingly used with new molecules to capture the biology of complex cancers and disease states, and to provide insight into the role of the immune system. The establishment of syngeneic mouse models requires the ability to generate surrogate mouse counterparts to antibodies designed for humans. In the field of bispecific antibodies, there remains a dearth of technologies available to generate native IgG-like mouse bispecific antibodies. Thus, we engineered a simple co-expression system for one-step purification of intact mouse IgG1 and IgG2a bispecific antibodies from any antibody pair. We demonstrated proof of concept with CD3/CD20 bispecific antibodies, which highlighted both the quality and efficacy of materials generated by this technology.

Protein identification and expression analysis using mass spectrometry.

The identification and quantification of the proteins that a whole organism expresses under certain conditions is a main focus of high-throughput proteomics. Advanced proteomics approaches generate new biologically relevant data and potent hypotheses. A practical report of what proteome studies can and cannot accomplish in common laboratory settings is presented here. The review discusses the most popular tandem mass-spectrometry-based methods and focuses on how to produce reliable results. A step-by-step description of proteome experiments is given, including sample preparation, digestion, labeling, liquid chromatography, data processing, database searching and statistical analysis. The difficulties and bottlenecks of proteome analysis are addressed and the requirements for further improvements are discussed. Several diverse high-throughput proteomics-based studies of microorganisms are described.

Experiment-specific estimation of peptide identification probabilities using a randomized database.

Determining the error rate for peptide and protein identification accurately and reliably is necessary to enable evaluation and crosscomparisons of high throughput proteomics experiments. Currently, peptide identification is based either on preset scoring thresholds or on probabilistic models trained on datasets that are often dissimilar to experimental results. The false discovery rates (FDR) and peptide identification probabilities for these preset thresholds or models often vary greatly across different experimental treatments, organisms, or instruments used in specific experiments. To overcome these difficulties, randomized databases have been used to estimate the FDR. However, the cumulative FDR may include low probability identifications when there are a large number of peptide identifications and exclude high probability identifications when there are few. To overcome this logical inconsistency, this study expands the use of randomized databases to generate experiment-specific estimates of peptide identification probabilities. These experiment-specific probabilities are generated by logistic and Loess regression models of the peptide scores obtained from original and reshuffled database matches. These experiment-specific probabilities are shown to very well approximate "true" probabilities based on known standard protein mixtures across different experiments. Probabilities generated by the earlier Peptide_Prophet and more recent LIPS models are shown to differ significantly from this study's experiment-specific probabilities, especially for unknown samples. The experiment-specific probabilities reliably estimate the accuracy of peptide identifications and overcome potential logical inconsistencies of the cumulative FDR. This estimation method is demonstrated using a Sequest database search, LIPS model, and a reshuffled database. However, this approach is generally applicable to any search algorithm, peptide scoring, and statistical model when using a randomized database.

Experimental standards for high-throughput proteomics.

Proteome analysis, utilizing high-throughput proteomics approaches, involves studying proteins that a whole organism (or specific tissue or cellular compartment) expresses under certain conditions. Intrinsic difficulties of these studies, as well as the enormous volumes of data they typically produce, make the proteome analysis and interpretation very difficult. As with any high-throughput approach, proteomics experiments should be carefully designed, analyzed, and verified. In addition to computational standards,experimental standards--simple and complex mixtures of known proteins--for high-throughput proteomics have to be developed and utilized. This article discusses such experimental standards and their implementations.

Randomized sequence databases for tandem mass spectrometry peptide and protein identification.

Tandem mass spectrometry (MS/MS) combined with database searching is currently the most widely used method for high-throughput peptide and protein identification. Many different algorithms, scoring criteria, and statistical models have been used to identify peptides and proteins in complex biological samples, and many studies, including our own, describe the accuracy of these identifications, using at best generic terms such as "high confidence." False positive identification rates for these criteria can vary substantially with changing organisms under study, growth conditions, sequence databases, experimental protocols, and instrumentation; therefore, study-specific methods are needed to estimate the accuracy (false positive rates) of these peptide and protein identifications. We present and evaluate methods for estimating false positive identification rates based on searches of randomized databases (reversed and reshuffled). We examine the use of separate searches of a forward then a randomized database and combined searches of a randomized database appended to a forward sequence database. Estimated error rates from randomized database searches are first compared against actual error rates from MS/MS runs of known protein standards. These methods are then applied to biological samples of the model microorganism Shewanella oneidensis strain MR-1. Based on the results obtained in this study, we recommend the use of use of combined searches of a reshuffled database appended to a forward sequence database as a means providing quantitative estimates of false positive identification rates of peptides and proteins. This will allow researchers to set criteria and thresholds to achieve a desired error rate and provide the scientific community with direct and quantifiable measures of peptide and protein identification accuracy as opposed to vague assessments such as "high confidence."