Accurate detection of RNA stem-loops in structurome data reveals widespread association with protein binding sites.

RNA molecules are known to fold into specific structures which often play a central role in their functions and regulation. In silico folding of RNA transcripts, especially when assisted with structure profiling (SP) data, is capable of accurately elucidating relevant structural conformations. However, such methods scale poorly to the swaths of SP data generated by transcriptome-wide experiments, which are becoming more commonplace and advancing our understanding of RNA structure and its regulation at global and local levels. This has created a need for tools capable of rapidly deriving structural assessments from SP data in a scalable manner. One such tool we previously introduced that aims to process such data is patteRNA, a statistical learning algorithm capable of rapidly mining big SP datasets for structural elements. Here, we present a reformulation of patteRNA's pattern recognition scheme that sees significantly improved precision without major compromises to computational overhead. Specifically, we developed a data-driven logistic classifier which interprets patteRNA's statistical characterizations of SP data in addition to local sequence properties as measured with a nearest neighbour thermodynamic model. Application of the classifier to human structurome data reveals a marked association between detected stem-loops and RNA binding protein (RBP) footprints. The results of our application demonstrate that upwards of 30% of RBP footprints occur within loops of stable stem-loop elements. Overall, our work arrives at a rapid and accurate method for automatically detecting families of RNA structure motifs and demonstrates the functional relevance of identifying them transcriptome-wide.

Microfluidic cap-to-dispense (µCD): a universal microfluidic-robotic interface for automated pipette-free high-precision liquid handling.

Microfluidic devices have been increasingly used for low-volume liquid handling operations. However, laboratory automation of such delicate devices has lagged behind due to the lack of world-to-chip (macro-to-micro) interfaces. In this paper, we have presented the first pipette-free robotic-microfluidic interface using a microfluidic-embedded container cap, referred to as a microfluidic cap-to-dispense (µCD), to achieve a seamless integration of liquid handling and robotic automation without any traditional pipetting steps. The µCD liquid handling platform offers a generic and modular way to connect the robotic device to standard liquid containers. It utilizes the high accuracy and high flexibility of the robotic system to recognize, capture and position; and then using microfluidic adaptive printing it can achieve high-precision on-demand volume distribution. With its modular connectivity, nanoliter processability, high adaptability, and multitask capacity, µCD shows great potential as a generic robotic-microfluidic interface for complete pipette-free liquid handling automation.

Polysiloxane layers created by sol-gel and photochemistry: ideal surfaces for rapid, low-cost and high-strength bonding of epoxy components to polydimethylsiloxane.

In this article we introduce and compare three techniques for low-cost and rapid bonding of stereolithographically structured epoxy components to polydimethylsiloxane (PDMS). In short, we first create a polysiloxane layer on the epoxy surface via silane surface coupling and polymerization. Afterwards, the modified epoxy surface can be bonded to a PDMS component at room temperature using a handheld corona discharger, which is a commonly used low-cost technique for bonding two PDMS components. Using these methods bonds of desirable strength can be generated within half an hour. Depending on the epoxy resin, we found it necessary to modify the silanization procedure. Therefore, we provide a total of three different silanization techniques that allow bonding of a wide variety of stereolithographically structurable epoxy resins. The first technique is a UV-light induced silanization process which couples a silane that contains an epoxy-ring ((3-glycidoxypropyl)trimethoxysilane (GPTMS)). For surfaces that cannot be modified with this silane we use dimethoxydimethylsilane (DMDMS). This silane can either be coupled to the surface by a sol-gel process or UV-light induced polymerisation. The sol-gel process which is a heat induced surface modification technique results in high bond strengths. Because of the heat which triggers the sol-gel process, this technique is limited to epoxy polymers with high glass transition temperatures. For the majority of stereolithographically structured epoxy resins which typically have glass transition temperatures of around 60 °C the light-induced bonding technique is preferable. For all three techniques we performed DIN EN-conform tensile testing demonstrating maximum bond strengths of up to 350 kPa which is comparable with bond strengths reported for PDMS-to-PDMS bonds. For all bond methods, long-term stability as well as hydrolytic stability was assessed.