Specific Biomolecular Interactions Research Articles

Vibrational spectroscopic profiling of biomolecular interactions between oak powdery mildew and oak leaves.

Oak powdery mildew, caused by the biotrophic fungus Erysiphe alphitoides, is a prevalent disease affecting oak trees, such as English oak (Quercus robur). While mature oak populations are generally less susceptible to this disease, it can endanger young oak seedlings and new leaves on mature trees. Although disruptions of photosynthate and carbohydrate translocation have been observed, accurately detecting and understanding the specific biomolecular interactions between the fungus and the leaves of oak trees is currently lacking. Herein, via hybrid Raman spectroscopy combined with an advanced artificial neural network algorithm, the underpinning biomolecular interactions between biological soft matter, i.e., Quercus robur leaves and Erysiphe alphitoides, are investigated and profiled, generating a spectral library and shedding light on the changes induced by fungal infection and the tree's defence response. The adaxial surfaces of oak leaves are categorised based on either the presence or absence of Erysiphe alphitoides mildew and further distinguishing between covered or not covered infected leaf tissues, yielding three disease classes including healthy controls, non-mildew covered and mildew-covered. By analysing spectral changes between each disease category per tissue type, we identified important biomolecular interactions including disruption of chlorophyll in the non-vein and venule tissues, pathogen-induced degradation of cellulose and pectin and tree-initiated lignification of cell walls in response, amongst others, in lateral vein and mid-vein tissues. Via our developed computational algorithm, the underlying biomolecular differences between classes were identified and allowed accurate and rapid classification of disease with high accuracy of 69.6% for non-vein, 73.5% for venule, 82.1% for lateral vein and 85.6% for mid-vein tissues. Interfacial wetting differences between non-mildew covered and mildew-covered tissue were further analysed on the surfaces of non-vein and venule tissue. The overall results demonstrated the ability of Raman spectroscopy, combined with advanced AI, to act as a powerful and specific tool to probe foliar interactions between forest pathogens and host trees with the simultaneous potential to probe and catalogue molecular interactions between biological soft matter, paving the way for exploring similar relations in broader forest tree-pathogen systems.

Glycan-Presenting Coacervates Derived from Charged Poly(active esters): Preparation, Phase Behavior, and Lectin Capture.

This study presents the preparation and phase behavior of glycan-functionalized polyelectrolytes for capturing carbohydrate-binding proteins and bacteria in liquid condensate droplets. The droplets are formed by complex coacervation of poly(active ester)-derived polyanions and polycations. This approach allows for a straightforward modular introduction of charged motifs and specifically interacting units; mannose and galactose oligomers are used here as first examples. The introduction of carbohydrates has a notable effect on the phase separation and the critical salt concentration, potentially by reducing the charge density. Two mannose binding species, concanavalin A (ConA) and Escherichia coli, are shown to not only specifically bind to mannose-functionalized coacervates but also to some degree to unfunctionalized, carbohydrate-free coacervates. This suggests non-carbohydrate-specific charge-charge interactions between the protein/bacteria and the droplets. However, when mannose interactions are inhibited or when non-binding galactose-functionalized polymers are used, interactions are significantly weakened. This confirms specific mannose-mediated binding functionalization and suggests that introducing carbohydrates reduces non-specific charge-charge interactions by a so far unidentified mechanism. Overall, the presented route toward glycan-presenting polyelectrolytes enables new functional liquid condensate droplets with specific biomolecular interactions.

Interplay of Depletion Forces and Biomolecular Recognition in the Hierarchical Assembly of Supramolecular Tubes.

Crowding effects have a profound impact on the hierarchical organization of cellular architectures. In the fields of systems chemistry and soft matter, this effect has not received much attention so far. Here, it is explored how poly(ethylene glycol) (PEG) as a crowding agent invokes depletion forces that act on synthetic supramolecular tubes. Hence, supramolecular tubes are pushed from their random orientation into hierarchically assembled bundles due to the PEG-induced crowded environment. The resulting morphology of formed bundled architectures can be tuned by the concentrations of both the supramolecular tubes and the PEG. The introduction of biotin groups at the surface of the tubes allows the engineering of biotin-streptavidin crosslinks between them. The order of introducing PEG and streptavidin in the system further affects the formed hierarchical assemblies, as well as their resistance toward dilution. The strategy described here provides a new route to establish hierarchically organized supramolecular architectures, combining crowding and specific biomolecular interactions, which shows the potential for controlling the structure of supramolecular materials and other soft matter systems.

Label-free biosensing of lignans for therapeutics using engineered model surfaces

The label-free interaction analysis of macromolecules and small molecules has increasing importance nowadays, both in diagnostics and therapeutics. In the blood vascular system, human serum albumin (HSA) is a vital globular transport protein with potential multiple ligand binding sites. Characterizing the binding affinity of compounds to HSA is essential in pharmaceutics and in developing new compounds for clinical application. Aryltetralin lignans from the roots of Anthriscus sylvestris are potential antitumor therapeutic candidates, but their molecular scale interactions with specific biomolecules are unrevealed. Here, we applied the label-free grating-coupled interferometry (GCI) biosensing method with a polycarboxylate-based hydrogel layer with immobilized HSA on top of it. With this engineered model surface, we could determine the binding parameters of two novel aryltetralin lignans, deoxypodophyllotoxin (DPT), and angeloyl podophyllotoxin (APT) to HSA. Exploiting the multi-channel referencing ability, the unique surface sensitivity, and the throughput of GCI, we first revealed the specific biomolecular interactions. Traditional label-free kinetic measurements were also compared with a novel, fast way of measuring affinity kinetics using less sample material (repeated analyte pulses of increasing duration (RAPID)). Experiments with well-characterized molecular interactions (furosemide to carbonic-anhydrase (CAII) and warfarin, norfloxacin to HSA) were performed to prove the reliability of the RAPID method. In all investigated cases, the RAPID and traditional measurement gave similar affinity values. In the case of DPT, the measurements and relevant modeling suggested two binding sites on HSA, with dissociation constant values of Kd1 = 1.8 ± 0.01 μM, Kd2 = 3 ± 0.02 μM. In the case of APT, the experiments resulted in Kd1 = 9 ± 1.7 μM, Kd2 = 28 ± 0.3 μM. The obtained binding values might suggest the potential medical application of DPT and APT without further optimization of their binding affinity to HSA. These results could be also adapted to other biomolecules and applications where sample consumption and the rapidity of the measurements are critical.

Nanoclusters with specific DNA overhangs: modifying configurability, engineering contrary logic pairs and the parity generator/checker for error detection.

The most promising alternative for next-generation molecular computers is biocomputing, which uses DNAs as its primary building blocks to perform a Boolean operation. DNA nanoclusters (NCs) have emerged as promising candidates for biosensing applications due to their unique self-assembly properties and programmability. It has been demonstrated that adding DNA overhangs to DNA NCs improves their adaptability in identifying specific biomolecular interactions. A recent proposal in DNA computing is the concept of "contrary logic pairs (CLPs)" executed by employing a DNA hybrid architecture as a universal platform. We have designed thymine overhang-modified DNA-templated NCs (T-Au/Ag NCs). These NCs serve as a chemosensing ensemble platform, where the presence of HgII ions mediates the formation of M-Au/Ag NCs. The resulting NCs exhibit the capability to drive elementary CLPs (YES, NOT, OR, NOR, INH and IMP) as well as complex logic operations (XOR and XNOR). Additionally, they can be utilized for advanced non-arithmetic DNA logic devices like a parity generator (pG) and a parity checker (pC) for "error detection". Bit errors are an unavoidable and common occurrence during any computing. A cascade of XOR operations was used to evaluate these errors by introducing the pG and pC at the transmitting (TX) and receiving (RX) ends in binary transmission, respectively, which has devastating implications for reliable logic circuits, especially in advanced logic computation. Moreover, an even/odd natural number from 0 to 9 distinguishable pC was designed based on a dual-source responsive computing platform. This work offers inspiring avenues for a cost-effective strategy to construct highly-intelligent DNA computing devices by enhancing the multi-input responsive single DNA platform concept.

Acoustic-Based Theranostic Probes Activated by Tumor Microenvironment for Accurate Tumor Diagnosis and Assisted Tumor Therapy.

Acoustic-based imaging techniques, including ultrasonography and photoacoustic imaging, are powerful noninvasive approaches for tumor imaging owing to sound transmission facilitation, deep tissue penetration, and high spatiotemporal resolution. Usually, imaging modes were classified into "always-on" mode and "activatable" mode. Conventional "always-on" acoustic-based probes often have difficulty distinguishing lesion regions of interest from surrounding healthy tissues due to poor target-to-background signal ratios. As compared, activatable probes have attracted attention with improved sensitivity, which can boost or amplify imaging signals only in response to specific biomolecular recognition or interactions. The tumor microenvironment (TME) exhibits abnormal physiological conditions that can be used to identify tumor sections from normal tissues. Various types of organic dyes and biomaterials can react with TME, leading to obvious changes in their optical properties. The TME also affects the self-assembly or aggregation state of nanoparticles, which can be used to design activatable imaging probes. Moreover, acoustic-based imaging probes and therapeutic agents can be coencapsulated into one nanocarrier to develop nanotheranostic probes, achieving tumor imaging and cooperative therapy. Satisfactorily, ultrasound waves not only accelerate the release of encapsulated therapeutic agents but also activate therapeutic agents to exert or enhance their therapeutic performance. Meanwhile, various photoacoustic probes can convert photon energy into heat under irradiation, achieving photoacoustic imaging and cooperative photothermal therapy. In this review, we focus on the recently developed TME-triggered ultrasound and photoacoustic theranostic probes for precise tumor imaging and targeted tumor therapy.

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology.

Biomolecular interactions play versatile roles in numerous cellular processesby regulating and coordinating functionally relevant biological events. Biomolecules such as proteins, carbohydrates, vitamins, fatty acids, nucleic acids, and enzymes are fundamental building blocks of living beings; they assemble into complex networks in biosystems to synchronize a myriad of life events. Proteins typically utilize complex interactome networks to carry out their functions; hence it is mandatory to evaluate such interactions to unravel their importance in cells at both cellular and organism levels. Toward this goal, we introduce a rapidly emerging technology, field-effect biosensing (FEB), to determine specific biomolecular interactions. FEB is a benchtop, label-free, and reliable biomolecular detection technique to determine specific interactions and uses high-quality electronic-based biosensors. The FEB technology can monitor interactions in the nanomolar range due to the biocompatible nanomaterials used on its biosensor surface. As a proof of concept, the protein-protein interaction (PPI) between heat shock protein 90 (Hsp90) and cell division cycle 37 (Cdc37) was elucidated. Hsp90 is an ATP-dependent molecular chaperone that plays an essential role in the folding, stability, maturation, and quality control of many proteins, thereby regulating multiple vital cellular functions. Cdc37 is regarded as a protein kinase-specific molecular chaperone, as it specifically recognizes and recruits protein kinases to Hsp90 to regulate their downstream signal transduction pathways. As such, Cdc37 is considered a co-chaperone of Hsp90. The chaperone-kinase pathway (Hsp90/Cdc37 complex) is hyper-activated in multiple malignancies promoting cellular growth; therefore, it is a potential target for cancer therapy. The present study demonstrates the efficiency of FEB technology using the Hsp90/Cdc37 model system. FEB detected a strong PPI between the two proteins (KD values of 0.014 µM, 0.053 µM, and 0.072 µM in three independent experiments). In summary, FEB is a label-free and cost-effective PPI detection platform, which offers fast and accurate measurements.

Water-powered self-propelled magnetic nanobot for rapid and highly efficient capture of circulating tumor cells

Nanosized robots with self-propelling and navigating capabilities have become an exciting field of research, attributable to their autonomous motion and specific biomolecular interaction ability for bio-analysis and diagnosis. Here, we report magnesium (Mg)-Fe3O4-based Magneto-Fluorescent Nanorobot (“MFN”) that can self-propel in blood without any other additives and can selectively and rapidly isolate cancer cells. The nanobots viz; Mg-Fe3O4-GSH-G4-Cy5-Tf and Mg-Fe3O4-GSH-G4-Cy5-Ab have been designed and synthesized by simple surface modifications and conjugation chemistry to assemble multiple components viz; (i) EpCAM antibody/transferrin, (ii) cyanine 5 NHS (Cy5) dye, (iii) fourth generation (G4) dendrimers for multiple conjugation and (iv) glutathione (GSH) by chemical conjugation onto one side of Mg nanoparticle. The nanobots propelled efficiently not only in simulated biological media, but also in blood samples. With continuous motion upon exposure to water and the presence of Fe3O4 shell on Mg nanoparticle for magnetic guidance, the nanobot offers major improvements in sensitivity, efficiency and speed by greatly enhancing capture of cancer cells. The nanobots showed excellent cancer cell capture efficiency of almost 100% both in serum and whole blood, especially with MCF7 breast cancer cells.

Liquid-Liquid Phase Separation in Biology: Specific Stoichiometric Molecular Interactions vs Promiscuous Interactions Mediated by Disordered Sequences.

Extensive studies in the past few years have shown that nonmembrane bound organelles are likely assembled via liquid-liquid phase separation (LLPS), a process that is driven by multivalent protein-protein and/or protein-nucleic acid interactions. Both stoichiometric molecular interactions and intrinsically disordered region (IDR)-driven interactions can promote the assembly of membraneless organelles, and the field is currently dominated by IDR-driven biological condensate formation. Here we discuss recent studies that demonstrate the importance of specific biomolecular interactions for functions of diverse physiological condensates. We suggest that phase separation based on combinations of specific interactions and promiscuous IDR-driven interactions is likely a general feature of biological condensation under physiological conditions.

Atomic Force Microscopy-Based Force Spectroscopy and Multiparametric Imaging of Biomolecular and Cellular Systems.

During the last three decades, a series of key technological improvements turned atomic force microscopy (AFM) into a nanoscopic laboratory to directly observe and chemically characterize molecular and cell biological systems under physiological conditions. Here, we review key technological improvements that have established AFM as an analytical tool to observe and quantify native biological systems from the micro- to the nanoscale. Native biological systems include living tissues, cells, and cellular components such as single or complexed proteins, nucleic acids, lipids, or sugars. We showcase the procedures to customize nanoscopic chemical laboratories by functionalizing AFM tips and outline the advantages and limitations in applying different AFM modes to chemically image, sense, and manipulate biosystems at (sub)nanometer spatial and millisecond temporal resolution. We further discuss theoretical approaches to extract the kinetic and thermodynamic parameters of specific biomolecular interactions detected by AFM for single bonds and extend the discussion to multiple bonds. Finally, we highlight the potential of combining AFM with optical microscopy and spectroscopy to address the full complexity of biological systems and to tackle fundamental challenges in life sciences.

Purification of protein therapeutics via high-affinity supramolecular host-guest interactions.

Efficient purification is crucial to providing large quantities of recombinant therapeutic proteins, such as monoclonal antibodies and cytokines. However, affinity techniques for manufacturing protein therapeutics that use biomolecule-conjugated agarose beads that harness specific biomolecular interactions suffer from issues related to protein denaturation, contamination and the need to maintain biomolecule-specific conditions for efficient protein capture. Here, we report a versatile and scalable method for the purification of recombinant protein therapeutics. The method exploits the high-affinity and controllable host-guest interactions between cucurbit[7]uril (CB[7]) and selected guests such as adamantylammonium. We show that the Herceptin (the brand name of trastuzumab, a monoclonal antibody drug used to treat breast cancer) and the much smaller cytokine interferon α-2a can be purified by site-specifically tagging them with adamantylammonium using the enzyme sortase A, followed by high-affinity binding with CB[7]-conjugated agarose beads and the recovery of the protein using a guest with a stronger affinity for CB[7]. The thermal and chemical stability of CB[7] beads and their scalability, recyclability and low cost may also make them advantageous for the manufacturing of biosimilars.

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.

Predicting interactions between proteins and other biomolecules solely based on structure remains a challenge in biology. A high-level representation of protein structure, the molecular surface, displays patterns of chemical and geometric features that fingerprint a protein's modes of interactions with other biomolecules. We hypothesize that proteins participating in similar interactions may share common fingerprints, independent of their evolutionary history. Fingerprints may be difficult to grasp by visual analysis but could be learned from large-scale datasets. We present MaSIF (molecular surface interaction fingerprinting), a conceptual framework based on a geometric deep learning method to capture fingerprints that are important for specific biomolecular interactions. We showcase MaSIF with three prediction challenges: protein pocket-ligand prediction, protein-protein interaction site prediction and ultrafast scanning of protein surfaces for prediction of protein-protein complexes. We anticipate that our conceptual framework will lead to improvements in our understanding of protein function and design.

DNA origami cryptography for secure communication

Biomolecular cryptography exploiting specific biomolecular interactions for data encryption represents a unique approach for information security. However, constructing protocols based on biomolecular reactions to guarantee confidentiality, integrity and availability (CIA) of information remains a challenge. Here we develop DNA origami cryptography (DOC) that exploits folding of a M13 viral scaffold into nanometer-scale self-assembled braille-like patterns for secure communication, which can create a key with a size of over 700 bits. The intrinsic nanoscale addressability of DNA origami additionally allows for protein binding-based steganography, which further protects message confidentiality in DOC. The integrity of a transmitted message can be ensured by establishing specific linkages between several DNA origamis carrying parts of the message. The versatility of DOC is further demonstrated by transmitting various data formats including text, musical notes and images, supporting its great potential for meeting the rapidly increasing CIA demands of next-generation cryptography.

Biomolecular Sensors Based on Microfluidics-Embedded Graphene Field-Effect Transistors

With the rapid pace of discovery of molecular biomarkers associated with cancer and other diseases, there is a need for bioanalytical techniques able to detect and quantify large panels of biomolecules, with high throughput and accuracy. Nanoelectronic sensors are emerging in this field due to their potential for improved sensitivity, parallelization and portability. In this presentation, I will introduce our recent progress in assembling nanoelectronic biomolecular sensors based on graphene field-effect transistor device arrays combined with microfluidic circuitry. In particular, I will present two designs targeting either DNA oligonucleotide sequences or antibody-antigen coupling, and I will describe their electrical signatures for specific and non-specific biomolecular interactions with the graphene material. Finally, I will discuss the electronic detection of breast cancer and leukemia biomarkers for clinical diagnostics applications.

MaSIF - Deciphering interaction fingerprints from protein molecular surfaces

Abstract Predicting interactions between proteins and other biomolecules purely based on structure is an unsolved problem in biology. A high-level description of protein structure, the molecular surface, displays patterns of chemical and geometric features that fingerprint a protein’s modes of interactions with other biomolecules. We hypothesize that proteins performing similar interactions may share common fingerprints, independent of their evolutionary history. Fingerprints may be difficult to grasp by visual analysis but could be learned from large-scale datasets. We present MaSIF, a conceptual framework based on a new geometric deep learning method to capture fingerprints that are important for specific biomolecular interactions. We showcase MaSIF with three prediction challenges: protein pocket-ligand prediction, protein-protein interaction site prediction, and ultrafast scanning of protein surfaces for prediction of protein-protein complexes. We anticipate that our conceptual framework will lead to improvements in our understanding of protein function and design.

Micro-Patterning of PEG-Based Hydrogels With Gold Nanoparticles Using a Reactive Micro-Contact-Printing Approach.

In this work a novel, relatively simple, and fast method for patterning of gold nanoparticles (Au NPs) on poly(ethylene glycol) (PEG)-based hydrogels is presented. In the hereby exploited reactive micro-contact printing (reactive-μ-CP) process, the surface of a micro-relief patterned PDMS-stamp is first functionalized with an amino-silane self-assembled monolayer (SAM), which is then inked with Au NPs. The stamp is subsequently brought into conformal contact with thiol-functionalized PEG-based hydrogel films. Due to the strong gold-thiol interactions the Au NPs are adequately and easily transferred onto the surfaces of these soft, multifunctional PEG hydrogels. In this way, defined μ-patterns of Au NPs on PEG hydrogels are achieved. These Au NPs patterns allow specific biomolecular interactions on PEG surfaces, and cell adhesion has been studied. Cells were found to effectively adhere only on Au NPs micro-patterns and to avoid the anti-adhesive PEG background. Besides the cell adhesion studies, these Au NPs μ-patterns can be potentially applied as biosensors in plasmon-based spectroscopic devices or in medicine, e.g., for drug delivery systems or photothermal therapies.

Focal molography is a new method for the in situ analysis of molecular interactions in biological samples.

Focal molography is a next-generation biosensor that visualizes specific biomolecular interactions in real time. It transduces affinity modulation on the sensor surface into refractive index modulation caused by target molecules that are bound to a precisely assembled nanopattern of molecular recognition sites, termed the 'mologram'. The mologram is designed so that laser light is scattered at specifically bound molecules, generating a strong signal in the focus of the mologram via constructive interference, while scattering at nonspecifically bound molecules does not contribute to the effect. We present the realization of molograms on a chip by submicrometre near-field reactive immersion lithography on a light-sensitive monolithic graft copolymer layer. We demonstrate the selective and sensitive detection of biomolecules, which bind to the recognition sites of the mologram in various complex biological samples. This allows the label-free analysis of non-covalent interactions in complex biological samples, without a need for extensive sample preparation, and enables novel time- and cost-saving ways of performing and developing immunoassays for diagnostic tests.

Editor's Highlight: Analysis of the Effects of Cell Stress and Cytotoxicity on In Vitro Assay Activity Across a Diverse Chemical and Assay Space.

Chemical toxicity can arise from disruption of specific biomolecular functions or through more generalized cell stress and cytotoxicity-mediated processes. Here, responses of 1060 chemicals including pharmaceuticals, natural products, pesticidals, consumer, and industrial chemicals across a battery of 815 in vitro assay endpoints from 7 high-throughput assay technology platforms were analyzed in order to distinguish between these types of activities. Both cell-based and cell-free assays showed a rapid increase in the frequency of responses at concentrations where cell stress/cytotoxicity responses were observed in cell-based assays. Chemicals that were positive on at least 2 viability/cytotoxicity assays within the concentration range tested (typically up to 100 μM) activated a median of 12% of assay endpoints whereas those that were not cytotoxic in this concentration range activated 1.3% of the assays endpoints. The results suggest that activity can be broadly divided into: (1) specific biomolecular interactions against one or more targets (eg, receptors or enzymes) at concentrations below which overt cytotoxicity-associated activity is observed; and (2) activity associated with cell stress or cytotoxicity, which may result from triggering specific cell stress pathways, chemical reactivity, physico-chemical disruption of proteins or membranes, or broad low-affinity non-covalent interactions. Chemicals showing a greater number of specific biomolecular interactions are generally designed to be bioactive (pharmaceuticals or pesticidal active ingredients), whereas intentional food-use chemicals tended to show the fewest specific interactions. The analyses presented here provide context for use of these data in ongoing studies to predict in vivo toxicity from chemicals lacking extensive hazard assessment.

Biomolecular templating of functional hybrid nanostructures using repeat protein scaffolds.

The precise synthesis of materials and devices with tailored complex structures and properties is a requisite for the development of the next generation of products based on nanotechnology. Nowadays, the technology for the generation of this typeof devices lacks the precision to determine their properties and is accomplished mostly by 'trial and error' experimental approaches. The use of bottom-up approaches that rely on highly specific biomolecular interactions of small and simple components is an attractive approach for the templating of nanoscale elements. In nature, protein assemblies define complex structures and functions. Engineering novel bio-inspired assemblies by exploiting the same rules and interactions that encode the natural diversity is an emerging field that opens the door to create nanostructures with numerous potential applications in synthetic biology and nanotechnology. Self-assembly of biological molecules into defined functional structures has a tremendous potential in nano-patterning and the design of novel materials and functional devices. Molecular self-assembly is a process by which complex 3D structures with specified functions are constructed from simple molecular building blocks. Here we discuss the basis of biomolecular templating, the great potential of repeat proteins as building blocks for biomolecular templating and nano-patterning. In particular, we focus on the designed consensus tetratricopeptide repeats (CTPRs), the control on the assembly of these proteins into higher order structures and their potential as building blocks in order to generate functional nanostructures and materials.

An optimized measurement chamber for cantilever array measurements in liquid incorporating an automated sample handling system

Micro- and nanomechanical analytical devices for diagnostics require small sample volumes, and stable and efficient clamping of the sensors for optimized bioassays. A fully automated device for the readout of the dynamic and static response of cantilevers in a physiological liquid environment including a sample handling system is presented. The device provides sequential readout of the static and dynamic mode providing the best signal to noise ratio for each individual cantilever. In the dynamic mode, it is possible to measure up to the 16th flexural resonance mode of vibration of a 500 μm long and 1 μm thick cantilever. The automated sample handling system enables the local injection of sub microliter volumes of sample with excellent reproducibility. Data demonstrating the response of the cantilevers to external stimuli highlight the sensitivity of the device and the importance of the use of reference cantilevers to decouple biologically relevant metrics from environmental effects. A specific biomolecular interaction of sensitised nanospheres on cantilever sensors with a mass resolution of ~50 picogram in liquid is shown. PACS numbers: 07.10 Mechanical instruments, 87.85 Biosensors, 47.85. Fluidic