Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples.

The advancement of sophisticated instrumentation in mass spectrometry has catalyzed an in-depth exploration of complex proteomes. This exploration necessitates a nuanced balance in experimental design, particularly between quantitative precision and the enumeration of analytes detected. In bottom-up proteomics, a key challenge is that oversampling of abundant proteins can adversely affect the identification of a diverse array of unique proteins. This issue is especially pronounced in samples with limited analytes, such as small tissue biopsies or single-cell samples. Methods such as depletion and fractionation are suboptimal to reduce oversampling in single cell samples, and other improvements on LC and mass spectrometry technologies and methods have been developed to address the trade-off between precision and enumeration. We demonstrate that by using a monosubstrate protease for proteomic analysis of single-cell equivalent digest samples, an improvement in quantitative accuracy can be achieved, while maintaining high proteome coverage established by trypsin. This improvement is particularly vital for the field of single-cell proteomics, where single-cell samples with limited number of protein copies, especially in the context of low-abundance proteins, can benefit from considering analyte complexity. Considerations about analyte complexity, alongside chromatographic complexity, integration with data acquisition methods, and other factors such as those involving enzyme kinetics, will be crucial in the design of future single-cell workflows.

A Hybrid Orbitrap-Nanoelectromechanical Systems Approach for the Analysis of Individual, Intact Proteins in Real Time.

Nanoelectromechanical systems (NEMS)-based mass spectrometry (MS) is an emerging technique that enables determination of the mass of individual adsorbed particles by driving nanomechanical devices at resonance and monitoring the real-time changes in their resonance frequencies induced by each single molecule adsorption event. We incorporate NEMS into an Orbitrap mass spectrometer and report our progress towards leveraging the single-molecule capabilities of the NEMS to enhance the dynamic range of conventional MS instrumentation and to offer new capabilities for performing deep proteomic analysis of clinically relevant samples. We use the hybrid instrument to deliver E. coli GroEL molecules (801 kDa) to the NEMS devices in their native, intact state. Custom ion optics are used to focus the beam down to 40 µm diameter with a maximum flux of 25 molecules/second. The mass spectrum obtained with NEMS-MS shows good agreement with the known mass of GroEL.

Nanomechanical mass measurements through feature-based time series clustering.

Recent years have seen explosive growth in miniaturized sensors that can continuously monitor a wide variety of processes, with applications in healthcare, manufacturing, and environmental sensing. The time series generated by these sensors often involves abrupt jumps in the detected signal. One such application uses nanoelectromechanical systems (NEMS) for mass spectrometry, where analyte adsorption produces a quick but finite-time jump in the resonance frequencies of the sensor eigenmodes. This finite-time response can lead to ambiguity in the detection of adsorption events, particularly in high event-rate mass adsorption. Here, we develop a computational algorithm that robustly eliminates this often-encountered ambiguity. A moving-window statistical test together with a feature-based clustering algorithm is proposed to automate the identification of single-event jumps. We validate the method using numerical simulations and demonstrate its application in practice using time-series data that are experimentally generated by molecules adsorbing onto NEMS sensors at a high event rate. This computational algorithm enables new applications, including high-throughput, single-molecule proteomics.

Tidyproteomics: an open-source R package and data object for quantitative proteomics post analysis and visualization.

BACKGROUND: The analysis of mass spectrometry-based quantitative proteomics data can be challenging given the variety of established analysis platforms, the differences in reporting formats, and a general lack of approachable standardized post-processing analyses such as sample group statistics, quantitative variation and even data filtering. We developed tidyproteomics to facilitate basic analysis, improve data interoperability and potentially ease the integration of new processing algorithms, mainly through the use of a simplified data-object. RESULTS: The R package tidyproteomics was developed as both a framework for standardizing quantitative proteomics data and a platform for analysis workflows, containing discrete functions that can be connected end-to-end, thus making it easier to define complex analyses by breaking them into small stepwise units. Additionally, as with any analysis workflow, choices made during analysis can have large impacts on the results and as such, tidyproteomics allows researchers to string each function together in any order, select from a variety of options and in some cases develop and incorporate custom algorithms. CONCLUSIONS: Tidyproteomics aims to simplify data exploration from multiple platforms, provide control over individual functions and analysis order, and serve as a tool to assemble complex repeatable processing workflows in a logical flow. Datasets in tidyproteomics are easy to work with, have a structure that allows for biological annotations to be added, and come with a framework for developing additional analysis tools. The consistent data structure and accessible analysis and plotting tools also offers a way for researchers to save time on mundane data manipulation tasks.

Optical phased array neural probes for beam-steering in brain tissue.

Implantable silicon neural probes with integrated nanophotonic waveguides can deliver patterned dynamic illumination into brain tissue at depth. Here, we introduce neural probes with integrated optical phased arrays and demonstrate optical beam steering in vitro. Beam formation in brain tissue is simulated and characterized. The probes are used for optogenetic stimulation and calcium imaging.

Implantable photonic neural probes for light-sheet fluorescence brain imaging.

Significance: Light-sheet fluorescence microscopy (LSFM) is a powerful technique for high-speed volumetric functional imaging. However, in typical light-sheet microscopes, the illumination and collection optics impose significant constraints upon the imaging of non-transparent brain tissues. We demonstrate that these constraints can be surmounted using a new class of implantable photonic neural probes. Aim: Mass manufacturable, silicon-based light-sheet photonic neural probes can generate planar patterned illumination at arbitrary depths in brain tissues without any additional micro-optic components. Approach: We develop implantable photonic neural probes that generate light sheets in tissue. The probes were fabricated in a photonics foundry on 200-mm-diameter silicon wafers. The light sheets were characterized in fluorescein and in free space. The probe-enabled imaging approach was tested in fixed, in vitro, and in vivo mouse brain tissues. Imaging tests were also performed using fluorescent beads suspended in agarose. Results: The probes had 5 to 10 addressable sheets and average sheet thicknesses < 16 µ m for propagation distances up to 300 µ m in free space. Imaging areas were as large as ≈ 240 µ m × 490 µ m in brain tissue. Image contrast was enhanced relative to epifluorescence microscopy. Conclusions: The neural probes can lead to new variants of LSFM for deep brain imaging and experiments in freely moving animals.

Integrated Neurophotonics: Toward Dense Volumetric Interrogation of Brain Circuit Activity-at Depth and in Real Time.

We propose a new paradigm for dense functional imaging of brain activity to surmount the limitations of present methodologies. We term this approach "integrated neurophotonics"; it combines recent advances in microchip-based integrated photonic and electronic circuitry with those from optogenetics. This approach has the potential to enable lens-less functional imaging from within the brain itself to achieve dense, large-scale stimulation and recording of brain activity with cellular resolution at arbitrary depths. We perform a computational study of several prototype 3D architectures for implantable probe-array modules that are designed to provide fast and dense single-cell resolution (e.g., within a 1-mm3 volume of mouse cortex comprising ∼100,000 neurons). We describe progress toward realizing integrated neurophotonic imaging modules, which can be produced en masse with current semiconductor foundry protocols for chip manufacturing. Implantation of multiple modules can cover extended brain regions.

Fully Integrated Time-Gated 3D Fluorescence Imager for Deep Neural Imaging.

This paper presents a device for time-gated fluorescence imaging in the deep brain, consisting of two on-chip laser diodes and 512 single-photon avalanche diodes (SPADs). The edge-emitting laser diodes deliver fluorescence excitation above the SPAD array, parallel to the imager. In the time domain, laser diode illumination is pulsed and the SPAD is time-gated, allowing a fluorescence excitation rejection up to O.D. 3 at 1 ns of time-gate delay. Each SPAD pixel is masked with Talbot gratings to enable the mapping of 2D array photon counts into a 3D image. The 3D image achieves a resolution of 40, 35, and 73 µm in the x, y, and z directions, respectively, in a noiseless environment, with a maximum frame rate of 50 kilo-frames-per-second. We present measurement results of the spatial and temporal profiles of the dual-pulsed laser diode illumination and of the photon detection characteristics of the SPAD array. Finally, we show the imager's ability to resolve a glass micropipette filled with red fluorescent microspheres. The system's 420 µm-wide cross section allows it to be inserted at arbitrary depths of the brain while achieving a field of view four times larger than fiber endoscopes of equal diameter.

Visible-light silicon nitride waveguide devices and implantable neurophotonic probes on thinned 200 mm silicon wafers.

We present passive, visible light silicon nitride waveguides fabricated on ≈ 100 µm thick 200 mm silicon wafers using deep ultraviolet lithography. The best-case propagation losses of single-mode waveguides were ≤ 2.8 dB/cm and ≤ 1.9 dB/cm over continuous wavelength ranges of 466-550 nm and 552-648 nm, respectively. In-plane waveguide crossings and multimode interference power splitters are also demonstrated. Using this platform, we realize a proof-of-concept implantable neurophotonic probe for optogenetic stimulation of rodent brains. The probe has grating coupler emitters defined on a 4 mm long, 92 µm thick shank and operates over a wide wavelength range of 430-645 nm covering the excitation spectra of multiple opsins and fluorophores used for brain stimulation and imaging.

A 512-Pixel, 51-kHz-Frame-Rate, Dual-Shank, Lens-less, Filter-less Single Photon Avalanche Diode CMOS Neural Imaging Probe.

We present an implantable single photon shank-based imager, monolithically integrated onto a single CMOS IC. The imager comprises of 512 single photon avalanche diodes distributed along two shanks, with a 6-bit depth in-pixel memory and an on-chip digital-to-time converter. To scale down the system to a minimally invasive form factor, we substitute optical filtering and focusing elements with a time-gated, angle-sensitive detection system. The imager computationally reconstructs the position of fluorescent sources within a three-dimensional volume of 3.4 mm × 600 µm × 400 µm.

Exotic states in a simple network of nanoelectromechanical oscillators.

Synchronization of oscillators, a phenomenon found in a wide variety of natural and engineered systems, is typically understood through a reduction to a first-order phase model with simplified dynamics. Here, by exploiting the precision and flexibility of nanoelectromechanical systems, we examined the dynamics of a ring of quasi-sinusoidal oscillators at and beyond first order. Beyond first order, we found exotic states of synchronization with highly complex dynamics, including weak chimeras, decoupled states, traveling waves, and inhomogeneous synchronized states. Through theory and experiment, we show that these exotic states rely on complex interactions emerging out of networks with simple linear nearest-neighbor coupling. This work provides insight into the dynamical richness of complex systems with weak nonlinearities and local interactions.

Single-particle mass spectrometry with arrays of frequency-addressed nanomechanical resonators.

One of the main challenges to overcome to perform nanomechanical mass spectrometry analysis in a practical time frame stems from the size mismatch between the analyte beam and the small nanomechanical detector area. We report here the demonstration of mass spectrometry with arrays of 20 multiplexed nanomechanical resonators; each resonator is designed with a distinct resonance frequency which becomes its individual address. Mass spectra of metallic aggregates in the MDa range are acquired with more than one order of magnitude improvement in analysis time compared to individual resonators. A 20 NEMS array is probed in 150 ms with the same mass limit of detection as a single resonator. Spectra acquired with a conventional time-of-flight mass spectrometer in the same system show excellent agreement. We also demonstrate how mass spectrometry imaging at the single-particle level becomes possible by mapping a 4-cm-particle beam in the MDa range and above.

Optogenetic manipulation of medullary neurons in the locust optic lobe.

The locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts ( Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered excitatory postsynaptic potentials and firing of a postsynaptic, looming-sensitive neuron, the lobula giant movement detector. These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects. NEW & NOTEWORTHY Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and elicits excitatory postsynaptic potentials and spiking in an identified postsynaptic target neuron, the lobula giant movement detector neuron. This technique allows the manipulation of neuronal activity in locust neural circuits using optogenetics.

Mass Spectrometry Using Nanomechanical Systems: Beyond the Point-Mass Approximation.

The mass measurement of single molecules, in real time, is performed routinely using resonant nanomechanical devices. This approach models the molecules as point particles. A recent development now allows the spatial extent (and, indeed, image) of the adsorbate to be characterized using multimode measurements ( Hanay , M. S. , Nature Nanotechnol. , 10 , 2015 , pp 339 - 344 ). This "inertial imaging" capability is achieved through virtual re-engineering of the resonator's vibrating modes, by linear superposition of their measured frequency shifts. Here, we present a complementary and simplified methodology for the analysis of these inertial imaging measurements that exhibits similar performance while streamlining implementation. This development, together with the software that we provide, enables the broad implementation of inertial imaging that opens the door to a range of novel characterization studies of nanoscale adsorbates.

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

Patterned photostimulation via visible-wavelength photonic probes for deep brain optogenetics.

Optogenetic methods developed over the past decade enable unprecedented optical activation and silencing of specific neuronal cell types. However, light scattering in neural tissue precludes illuminating areas deep within the brain via free-space optics; this has impeded employing optogenetics universally. Here, we report an approach surmounting this significant limitation. We realize implantable, ultranarrow, silicon-based photonic probes enabling the delivery of complex illumination patterns deep within brain tissue. Our approach combines methods from integrated nanophotonics and microelectromechanical systems, to yield photonic probes that are robust, scalable, and readily producible en masse. Their minute cross sections minimize tissue displacement upon probe implantation. We functionally validate one probe design in vivo with mice expressing channelrhodopsin-2. Highly local optogenetic neural activation is demonstrated by recording the induced response-both by extracellular electrical recordings in the hippocampus and by two-photon functional imaging in the cortex of mice coexpressing GCaMP6.

Nanofabricated Neural Probes for Dense 3-D Recordings of Brain Activity.

Computations in brain circuits involve the coordinated activation of large populations of neurons distributed across brain areas. However, monitoring neuronal activity in the brain of intact animals with high temporal and spatial resolution has remained a technological challenge. Here we address this challenge by developing dense, three-dimensional (3-D) electrode arrays for electrophysiology. The 3-D arrays constitute the front-end of a modular and configurable system architecture that enables monitoring neuronal activity with unprecedented scale and resolution.

Frequency fluctuations in silicon nanoresonators.

Frequency stability is key to the performance of nanoresonators. This stability is thought to reach a limit with the resonator's ability to resolve thermally induced vibrations. Although measurements and predictions of resonator stability usually disregard fluctuations in the mechanical frequency response, these fluctuations have recently attracted considerable theoretical interest. However, their existence is very difficult to demonstrate experimentally. Here, through a literature review, we show that all studies of frequency stability report values several orders of magnitude larger than the limit imposed by thermomechanical noise. We studied a monocrystalline silicon nanoresonator at room temperature and found a similar discrepancy. We propose a new method to show that this was due to the presence of frequency fluctuations, of unexpected level. The fluctuations were not due to the instrumentation system, or to any other of the known sources investigated. These results challenge our current understanding of frequency fluctuations and call for a change in practices.

A National Network of Neurotechnology Centers for the BRAIN Initiative.

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As "brain observatories," these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them.