Copyright by Sertan Kutal Gokce 2016
The Dissertation Committee for Sertan Kutal Gokce Certifies that this is the approved version of the following dissertation:
Parallel and Serial Microfluidic Platforms for Femtosecond Laser Axotomy in Caenorhabditis elegans for Nerve Regeneration Studies
Committee:
Adela Ben-Yakar, Supervisor
Mikhail A. Belkin
Andrew Dunn
Mark F. Hamilton
Jon Pierce-Shimomura
Preston S. Wilson Parallel and Serial Microfluidic Platforms for Femtosecond Laser Axotomy in Caenorhabditis elegans for Nerve Regeneration Studies
by
Sertan Kutal Gokce, B.S.; M.S.
Dissertation Presented to the Faculty of the Graduate School of The University of Texas at Austin
in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
The University of Texas at Austin May 2016 Dedication
Annem Arife Çay’a, memleketim Adana’ya ve Galatasaray’a.
To my mom Arife Çay, my hometown Adana, and Galatasaray. Acknowledgements
First, I would like to thank my advisor Dr. Adela Ben-Yakar for her guidance, encouragement, and financial support throughout my Ph.D. studies at The University of Texas at Austin. Her enthusiasm and passion for multidisciplinary research and neuroscience have inspired numerous great projects such as the ones described here. I would like to thank my committee members Dr. Mikhail Belkin, Dr. Andrew Dunn, Dr. Mark F. Hamilton, Dr. Jon Pierce-Shimomura, and Dr. Preston S. Wilson. They have been supportive throughout my Ph.D. study. In particular, my most sincere appreciation is extended to Dr. Jon Pierce-Shimomura and Dr. Preston S. Wilson for their help and guidance during my Ph.D. studies and their valuable advice for my future career. I wish to thank all my past and present fellow lab members for making this Ph.D. journey interesting and fun and for providing their support when I struggled. I would like to thank especially Dr. Onur Ferhanoglu, Dr. Sudip Mondal, Dr. N. Ghorashian, Travis Jarrell, Aubri Kottek, Dr. Sudip Mondal, Dr. Ryan Doonan, Dr. Ki Hyun Kim, Dr. Neil Everett, Evan Hegarty, Christopher Michael Martin, Dr. Frederic Bourgeois, Sam Aminfard, Dr. Ilan Gabay, Dr. Dan Eversole, Peisen Zhao, Kaushik Subramanian, and Dr. Fred Li.
Next, I would like to thank all JPS lab members, especially Dr. Luisa Scott, Dr. Andres Vidal-Gadea, Sarah Nordquist, and Claire Celia Beron for always being helpful and listening to my problems regarding research. Next, I would like to thank Dr. Sydney Geissler, Anna Warden, and Roberto Ulises Cofresí for helping me with editing my dissertation and for answering my questions regarding biology.
v My sincere appreciation is extended to my dear friends Dr. Onur Kacar, Hande Gerkus, Dr. Yiorgos Zalachoris, Elif Zeynep Iyriboz, Dr. Can Hankendi, Batur Isdiken, Dr. Sanjiv Shah, Funda Donmez, Onur Domanic, Gokhan Yildiz, and Quack’s Bakery crew. I want to thank them for making my life in Austin joyful and sharing my Ph.D. journey. I want to thank my good friends in Turkey, who shared my Ph.D. journey over a very long distance. I want to thank Denizcan Soner, Umut Toklu, Murat Atak, Sabit Sagir, Emre Aytekin, Baran Evliyaoglu, Can Yagli, Fidel Berber, Onder Ucar, Utku Ozkan, Onur Gokpinar, Ilker Gezer, Mert Pala, Arda Bahadir, and Sencer Ucar. Last, but never the least, I would like to declare my deepest appreciation and greatest gratitude to my father, Salih Gökçe, my wonderful mom, Arife Çay, my grandparents who always believed in me and wanted me to pursue higher education, Ali Şahin Çay and Hatice Çay, my super aunt, Mürüvvet Çay, my aunts, Sacide Çay and Ülviye Gürbüz, my uncle, Yasin Çay. I do not believe I would ever have been able to seek higher education without your endless support and love. I also wish to recognize the many people that have made this dissertation a reality. In addition, I apologize in advance for the many people who I forgot to thank here.
vi Parallel and Serial Microfluidic Platforms for Femtosecond Laser Axotomy in Caenorhabditis elegans for Nerve Regeneration Studies
Sertan Kutal Gokce, Ph.D. The University of Texas at Austin, 2016
Supervisor: Adela Ben-Yakar
Understanding the molecular basis of nerve regeneration can potentiate the development of novel and efficient treatments for neurodegenerative diseases. Severing axons in the small nematode Caenorhabditis elegans (C. elegans) with femtosecond laser surgery and then observing the subsequent axonal regrowth is a promising approach to understand the molecular mechanisms of nerve regeneration in vivo. Effective and reversible immobilization of the nematodes is necessary for both axotomy and follow-up imaging. However, conventional worm handling techniques such as using anesthetics or polystyrene beads are labor-intensive and time-consuming processes, hindering high- throughput. Microfluidic devices enable the manipulation of the nematodes on a single chip with unprecedented throughput and integrity. This dissertation introduces two comprehensive microfluidic systems for femtosecond laser axotomy in C. elegans, offering several advantages over conventional techniques in terms of speed and the ability for automation of the tedious axotomy experiments. The first microfluidic system is an automated serial microfluidic platform for vii performing femtosecond laser axotomy in C. elegans. The microfluidic platform along with a custom-developed automation program isolates a single nematode from a pre-loaded population, immobilizes the nematode, and performs femtosecond laser axotomy. The full automation of the axotomy process is achieved by combining efficient image analysis methodologies with synchronized valve and flow progression in the microfluidic chip to perform multiple surgeries in a serial and automated manner. The serial automated microfluidic platform reduces the time required to perform axotomies within individual worms to ~ 17 s/worm. The second microfluidic system is a parallelized multitrap microfluidic platform, “worm hospital”, that allows on-chip axotomy, post-surgery housing for recovery, and imaging of nerve regeneration on a single chip. The microfluidic platform features 20 trapping channels for laser axotomy and subsequent post-surgery imaging, and a perfusion area to house the worms after laser axotomy. This microfluidic platform is a single-flow
Polydimethylsiloxane (PDMS) layer device and has no active control PDMS layer, which reduces the fabrication and operation complexity of the chip, especially for non-expert users. The roles of neurodevelopmental genes in the Wnt/Frizzled pathway on the nerve regeneration was investigated using the “worm hospital”. In summary, the microfluidic platforms presented in this dissertation enabled performing femtosecond laser axotomy in C. elegans in a fast and repeatable manner with a controllable microenvironment. Both microfluidic platforms offer promising methodologies for prospective large-scale screening of genes involved in nerve regeneration with a high throughput in an automated manner.
viii Table of Contents
List of Tables ...... xii
List of Figures ...... xiii
Chapter 1: Introduction ...... 1 1.1 Dissertation overview and objectives ...... 2
Chapter 2: Background ...... 4 2.1. C. elegans as a model organism:...... 4 2.2 Femtosecond laser ablation ...... 5 2.3 Femtosecond laser axotomy in C. elegans ...... 7 2.4 Microfluidics Overview ...... 8 2.5 Microfluidic devices for C. elegans research ...... 11
Chapter 3: The Fully Automated Serial Femtosecond Laser Axotomy Chip ...... 15 3.1 Introduction ...... 15 3.2 System Overview ...... 17 3.3 Microfluidic Device Design ...... 19 3.4 Progression of valve actuation, flow, and worm manipulation processing25 3.5 Image processing methodology for automated identification of neurons and targeting for laser axotomy ...... 28 3.5.1 Step 1: Identification of the worm location ...... 31 3.5.2 Step 2: Detection of a neuronal cell body in the small FOV ...... 33 3.5.3 Step 3: Verification of neuron of interest ...... 35 3.5.4 Step 4: Laser axotomy ...... 38 3.6 Characterization of the automated platform ...... 39 3.6.1 Effect of chip manipulation on worm survivability ...... 39 3.6.2 Timing and axotomy success rates ...... 40 3.6.3 Automated on-chip surgery axonal reconnection rates ...... 44 3.7 Experimental Procedures ...... 46 3.7.1 Device fabrication methods ...... 46 3.7.2 Opto-mechanical setup...... 48 ix 3.7.3 C. elegans maintenance ...... 50 3.7.4 Laser axotomies and post-surgical imaging on agar pads ...... 51 3.7.5 Microfluidic chip priming and preparation for axotomies ...... 51 3.8 Conclusions ...... 52
Chapter 4: A Microfluidic “Worm Hospital” for Axotomy, Recovery, and Imaging of Caenorhabditis Elegans ...... 54 4.1. Introduction ...... 54 4.2. Device design and operation ...... 57 4.2.1. Microfluidic device design ...... 57 4.2.2. Microfuidic flow process ...... 61 4.3. Results ...... 62 4.3.1. Trapping and orientation characterization ...... 62 4.3.2. Viability test ...... 67 4.3.3. Axonal regeneration results ...... 69 4.3.4. Axonal growth and guidance, and neuronal polarity genes ...... 71 4.4 Experimental Methods ...... 77 4.4.1 Device fabrication ...... 77 4.4.2. Opto-mechanical setup...... 78 4.4.3. System operation and control...... 79 4.4.4 Laser axotomy and post-surgical imaging ...... 80 4.4.5 Nematode maintenance ...... 80 4.4.5. Neuronal RNAi hypersensitive strain for axotomy assays ...... 81 4.4.6. On-chip immobilization with the aid of levamisole ...... 82 4.5 Conclusions ...... 83
Chapter 5: Conclusions and Future Work ...... 85 5.1 Summary of the dissertation ...... 85 5.2 Future Work ...... 86
x Appendix A: Supplementary Software Document for the Serial Automated Microfluidic Femtosecond Laser Axotomy Platform for Nerve Regeneration Studies in C. elegans ...... 88 A.1 Software Instructions and List of Hardware Requirements: ...... 88 A.2 Hardware list ...... 88 A.3 Axotomy.vi ...... 89 A.3.1. START Tab (Figure A.1): ...... 91 A.3.2. CCD Camera Tab (Figure A.2): ...... 91 A.3.3 Motorized Stage Tab (Figure A.3): ...... 93 A.3.4 Shutter Tab (Figure A.4): ...... 95 A.3.5 Piezo Stage Tab (Figure A.5):...... 96 A.3.6 Valves Tab (Figures A.6-A.12): ...... 97 A.3.7 ROI Locations (Figure A.13): ...... 107 A.3.8 Automated Process Tab (Figure A.14): ...... 107
REFERENCES ...... 109
xi List of Tables
Table 4.1: Comparison of on-chip and on-agar axonal reconnection percentages of
ALM neurons in single mutant and RNAi experiments...... 71 Table 4.2: Comparison of on-chip and on-agar axonal reconnection percentages of
PLM neurons in single mutant and RNAi experiments...... 71 Table 4.3: On-chip axonal reconnection percentages of ALM neurons in single
mutant animals...... 73 Table 4.2: On-chip axonal reconnection percentages of ALM neurons with RNAi
gene knockdown...... 74 Table 4.5: On-chip axonal reconnection percentages of PLM neurons in single mutant
animals...... 75 Table 4.6: On-chip axonal reconnection percentages of PLM neurons with RNAi gene
knockdown...... 75
xii List of Figures
Figure 2.1: The schematic view of Larval 1 (L1) stage of C. elegans...... 5 Figure 2.2: Illustration of the series of mechanisms involved in plasma-induced
optical breakdown ...... 6
Figure 2.3: Femtosecond laser axotomy in C. elegans ...... 8
Figure 2.4: Fabrication process flow of multilayer soft lithography ...... 10
Figure 2.5: Two basic configurations for multi-layer microfluidic valves...... 11
Figure 2.6: Recent examples of microfluidic laser surgery platforms...... 14
Figure 3.1: Axotomy chip overview...... 18
Figure 3.2: Worm delivery challenges in the trapping area ...... 20 Figure 3.3: Flow direction in T-shaped staging/trapping area and 3D interconnects.
...... 24
Figure 3.4: Automated progression of valve actuation and flow...... 26
Figure 3.5: The soft touch neurons of C. elegans: ...... 29
Figure 3.6: Automation Flowchart...... 30 Figure 3.7: Image processing methodology for identifying the worm location within
the trapping area (Step 1)...... 32 Figure 3.8: The circular object detection methodology to detect a cell body in the
field of view (Step 2)...... 34 Figure 3.9: Fine focusing methodology to verify the neuron of interest and determine
the orientation of the axon...... 36 Figure 3.10: Image processing steps to verify the neuron of interest (Step 3), locate
the target on the desired axon, and perform laser axotomy (Step 4).37
Figure 3.11: Lifespan analysis...... 40
xiii Figure 3.12: Average process timings per worm for different experiments ...... 41
Figure 3.13: Success rate and timing performance of the automation...... 43
Figure 3.14: Imaging of regrowing axons of interest 24 hours after surgery...... 45
Figure 3.15: Axonal reconnection results...... 46
Figure 3.16: Schematic of the serial automated laser axotomy setup...... 50
60
Figure 4.1: Worm Hospital overview...... 60
Figure 4.2: The flow progress on the serial microfluidic chip ...... 62
Figure 4.3: Trapping and retrapping efficiency characterization ...... 66
67
Figure 4.4: Head-tail orientation characterization...... 67
Figure 4.5: Lifespan analysis...... 68 Figure 4.6: On-chip imaging of axonal regrowth and reconnection 24 h after surgery,
and comparison of on-chip axotomy performance to on-agar axotomy
using anesthetics...... 70 Figure 4.7: On-chip axonal reconnection results for the selected genes in
WNT/Frizzled family...... 76
Figure A.1: The front panel of Axotomy.vi with “START” tab chosen...... 90
Figure A.2: “CCD Camera” Tab...... 92
Figure A.3: “Motorized Stage” Tab...... 94
Figure A.4: “Shutter” Tab...... 96
Figure A.5: “Piezo Stage” Tab...... 97
Figure A.6: “Valves” tab and “Main Valve Control” sub-tab chosen...... 100
Figure A.7: Two elements of Pre-Loading Sequence: ...... 101
Figure A.8: Four elements of the Injection Sequence: ...... 102 xiv Figure A.9: Immobilization Sequence: ...... 103
Figure A.10: Two Elements of Ejection Sequence: ...... 104 b) 105
Figure A.11: Two Elements of Flush Sequence: ...... 105
Figure A.12: Elements of cleaning sequence: ...... 106
Figure A.13: The front panel of Axotomy.vi with “ROI Locations” tab chosen. 107 Figure A. 14: The front panel of Axotomy.vi with “Automated Process” Tab chosen.
...... 108
xv Chapter 1: Introduction
The limited ability of neurons to regenerate, especially in the mature central nervous system (CNS), leads to permanent deficiencies in the nervous system after an injury [1, 2]. The inability of neurons to regrow after an injury is attributed to both intrinsic [3-5] and extrinsic [6-8] mechanisms. Despite many efforts to understand the mystery behind nerve regeneration, the molecular mechanisms of neural regrowth still remains elusive. Understanding these mechanisms could lead to the development of novel and effective therapeutics for brain trauma, stroke, Parkinson’s disease, Alzheimer’s disease, and other neurodegenerative illnesses. These disorders affect countless people globally, leading to an excess economic and social burden worldwide [9, 10]. A promising approach of elucidating the molecular basis of regeneration in vivo is to severe axons in the small model organism Caenorhabditis elegans (C. elegans) and observe the post-surgery regeneration. Specifically, nerve regeneration and degeneration processes can be studied by axotomizing the neurons of living and intact C. elegans with ultrafast laser axotomy [11]. Since the first demonstration of the successful regeneration of neurons after femtosecond laser axotomy [11], this technique has spurred many studies to understand the molecular basis of in vivo nerve regeneration [3, 12-20]. The advantage of femtosecond laser surgery is its ability to create a sub-micron ablation volume with minimal damage to the surrounding tissue, which permits the study of nerve regeneration after the surgery in vivo. However, nerve regeneration studies in living C. elegans have been hampered by the duration and complexity of this method, since laser axotomy requires immobilization of the worm so that the axon of interest can be precisely positioned within the focal volume of the laser beam. In addition, a complete immobilization of the nematodes is required for high-resolution imaging of the
1 regenerating axons post injury. Conventional immobilization methods include anesthetics [3, 18, 21], polystyrene beads [22, 23], and gluing worms [24]. Gluing worms is not a viable option for nerve regeneration studies because the worms cannot be recovered for post-injury follow-ups. Other methods require manually orienting nematodes with a platinum tip to get the neuron of interest near the glass cover slip interface. These tasks must be accomplished without losing or harming the animals during their recovery from anesthetics or polystyrene beads via liquid buffer exchange [11, 22]. These conventional immobilization techniques require picking, sorting, and transferring of individual worms, hindering the throughput of the axotomy experiments. Using the conventional techniques, large-scale assays of nerve regeneration studies such as gene knockout and RNA interference (RNAi) would take years to complete. Advancements in the capability of microfluidic technologies of fluid enabled manipulation of handling small volumes an automated, precise, and consistent fashion. Since the dimensions of the nematode’s body are in the micron to millimeter scale, the worms can be processed using microfluidic platforms that provide a controllable experimental environment and can enhance the automation of worm handling processes. To increase the throughput and improve the repeatability of experiments, the microfluidic technology has been used for a variety of C. elegans studies. Consequently, microfluidic platforms along with the automation hold a great promise of increasing throughput of axotomy experiments in C. elegans.
1.1 DISSERTATION OVERVIEW AND OBJECTIVES
The primary objective of this dissertation is to develop and test integrated, novel microfluidic platforms that allow femtosecond laser axotomy and imaging of post-recovery nerve regeneration in C. elegans in a rapid and controllable manner to understand molecular mechanisms behind nerve regeneration.
2 Chapter 2 first gives a brief review of the use of C. elegans as a model organism and examples of femtosecond laser axotomy in C. elegans. Then, microfluidic platforms for C. elegans assays and on-chip axotomy of C. elegans platforms are detailed, along with a comparison of traditional axotomy and on-chip axotomy techniques. Chapter 3 presents the development and implementation of the fully automated serial microfluidic platform. Particular attention is paid to the unique features of the axotomy platform enabling full automation of the process and the development of a custom-developed automation software to sever axons of the nematodes. Then, the success rates of and average timing for each automation step are presented. Finally, a comparison of axonal reconnection rates of on-chip and on-agar experiments using anesthetics are given for two different ablation energy conditions. Chapter 4 presents the design and characterization of the parallelized multitrap microfluidic platform, the “worm hospital”, that allows on-chip axotomy, post-surgery housing for recovery, and imaging of nerve regeneration on a single chip. First, the fluidic design of the chip is detailed. Particular focus is given on the on-chip trapping and retrapping efficiencies. Finally, the role of neurodevelopmental genes in the Wnt/Frizzled pathway on the regenerative capacity of the anterior lateral microtubule cells (ALM) and the posterior lateral microtubule cells (PLM) neurons is presented by utilizing the “worm hospital”. Chapter 5, the last chapter, summarizes the dissertation work and discusses the future research.
3 Chapter 2: Background
This chapter presents the background information on the scientific methodologies used in this dissertation. This chapter introduces the model organism (C. elegans) and emphasizes its use for nerve regeneration studies. Then, an introduction to microfluidic technology and related valve configurations is given. Lastly, information on microfluidic assays that address different biological problems will be presented, highlighting how the development of laser axotomy chips has advanced nerve regeneration studies in C. elegans.
2.1. C. ELEGANS AS A MODEL ORGANISM:
Since its introduction to the scientific community, the nematode C. elegans (see Figure 2.1) has been widely used as a model organism [25-27]. The small roundworm has been studied across a variety of fields of the biological sciences, such as development [28- 30], behavior [31-41], metabolism [42-46] and neurodegenerative diseases [47-51]. The interest in C. elegans research owes to both the simplicity and complexity of the nematode. First, the roundworm C. elegans can be easily bred in laboratory conditions. The animals can grow on agar plates seeded with Escherichia coli [52] or they can also grow in liquid cultures with bacteria (S-medium), which allows high-throughput assays [53-56]. Moreover, the development of worms from egg to adult stage of (~ 1 mm in length) occurs within only 3 days [57]. Second, due to its small size, short generation time, and mostly self-fertilizing reproduction, assays can be easily carried out on large isogenic populations. Third, the nematode has a transparent body that allows the optical interrogation of individual cells throughout the lifespan of the wormss. Fourth, C. elegans have one of the simplest and the best characterized nervous systems of any model organisms, and the entire neural circuitry is mapped [58], making the study of single neurons possible. Hermaphrodite nematodes have 302 neurons and males have 381 neurons along with male-
4 specific neurons [52]. Despite the small number of neurons, nematodes possess a wide range of complex behavioral modalities such as thermotaxis [59], chemotaxis [60], and odortaxis [36, 61], which all be studied in molecular and cellular detail [62]. Fifth, C. elegans is the first multicellular organism with a fully sequenced genome [63]. Moreover, highly significant genetic homology with humans [64-67], many conserved biological processes [49, 57, 68], and genetic amenability of C. elegans make the nematode an emergent model organism for drug discoveries for human diseases.
Figure 2.1: The schematic view of Larval 1 (L1) stage of C. elegans. The schematic shows the distinct body parts and the principal parts of the nervous system. The image is adapted from [69].
2.2 FEMTOSECOND LASER ABLATION
As the light intensity becomes higher, nonlinear effects become prominent, such as self-phase modulation, self-focusing, multiphoton absorption, and laser-induced optical breakdown [70]. Ultrafast laser technology offers very precise ablation capability with its ability to reach high peak power intensities that leads to lower ablation threshold values
[71, 72]. Precise ablation of a variety of materials has been shown using femtosecond near- infrared laser techniques [73-75].
5 The principle mechanism behind the low-energy and precise femtosecond laser ablations is the laser-induced optical breakdown [70, 71, 73]. Femtosecond laser ablation of transparent materials happens through a series of multi-photon absorption, tunneling, and avalanche ionization [72, 76]. First, the multiphoton absorption by the material is required to ionize an electron (Figure 2.2). Ionized electron becomes a seed for avalanche ionization, it starts absorbing more photons linearly and gaining kinetic energy through the multiple Inverse Bremsstrahlung process [76]. When the energy of the ionized electron reaches between approximately 1.5-2 times of the band gap energy, it can produce another free electron by impact ionization [72, 76]. The free electron density increases exponentially through avalanche ionization, leading to formation of a high density plasma within the focal volume. The exponential growth continues until the electron density reaches a critical limit where the frequencies of the plasma and incident laser beam match. Then the electron plasma passes on high kinetic energy to the ions, which leads to meting and vaporization of the material.
Figure 2.2: Illustration of the series of mechanisms involved in plasma-induced optical breakdown The ionization of valence electrons can occur through multiphoton absorption. A high density of ionized electrons are obtained through multiple Inverse Bremsstrahlung absorption, which is followed by impact ionization. The image is adapted from [76]. 6 2.3 FEMTOSECOND LASER AXOTOMY IN C. ELEGANS
It was only recently discovered that C. elegans neurons can regenerate shortly after the severing of an individual axons with the femtosecond laser ablation [11]. By focusing ultrafast laser pulses, Yanik et al. showed that it is possible to precisely sever a single axon in living and intact C. elegans without damaging the surrounding tissue [11]. Interestingly, the injured neurons could spontaneously regenerate within 24 hours of the laser axotomy, accompanied by functional recovery as in Figure 2.2. This method has been successfully adapted by the C. elegans community since its first demonstration twelve years ago [3, 12- 18, 77]. Axons have the ability to regenerate after being severed and regain their functionality in the nervous system. The regeneration process after an injury leads to changes in gene transcription and local protein synthesis. The process is regulated by different factors such as phylogenetically conserved pathways [78, 79], the neuronal environment [80], and the intrinsic state of the neuron [78, 81]. However, the roles of most of these components remain a matter of debate. Several studies have attempted to clarify the role of these components in nerve regeneration. However, these studies were limited to large animal models [82-87], which ultimately did not elucidate the regulatory mechanisms due to the lack of an adequate nerve injury method available only in these organisms. An organism with a simpler nervous system such as C. elegans¸ provides a feasible path towards studying molecular mechanisms behind nerve regeneration. The importance of using C. elegans as a nerve regeneration model is that several pathways affecting vertebrate axon outgrowth in humans have been found to shows similar effects in C. elegans [3, 30, 78]. There have been only two large-scale genetic screenings to identify pathways associated with axon regeneration in C. elegans [3, 17]. Despite the unprecedented scale of these studies, a large fraction of the worm’s genome still needs to 7 be tested for nerve regeneration pathways. This requirement can only be realistically met using high-throughput manipulation and axotomy platforms.
Figure 2.3: Femtosecond laser axotomy in C. elegans Fluorescence images of axons labelled with GFP before, immediately after, and in the hours following axotomy. The image is adapted from [11].
2.4 MICROFLUIDICS OVERVIEW
Microfluidic devices enable manipulation of fluids at the micron to nanometer scale in a controllable environment. Moreover, they provide a platform to perform precise experiments in life sciences with minimal use of chemical and biological reagents. The first microfluidic chips were made of silicon or glass [88, 89]. Typically, wet etching or deep reactive ion etching (DRIE) tools were employed to create channels of varying geometries in the substrate of choice for the desired application [90]. These etching processes were both time consuming, and labor-intensive. This was due to the need to perform photolithography and etching with advanced dry etching tools, and harsh chemicals for every batch of devices made. Dr. George Whiteside’s group developed a new lithography technique based on replicas of the silicon master molds using polydimethylsiloxane (PDMS) [91]. In soft lithography, typically, a pattern is defined in a photolithographic mask that is used to generate the pattern in a photosensitive material 8 (photoresist) that has been spin-coated onto a silicon wafer surface. The photoresist on the silicon wafer is used as the mold for PDMS or another chosen elastomer [92, 93]. The elastomer is cured on the silicon mold for hardening and then is peeled of the master mold (silicon wafer). The hardened elastomer is then bonded to glass, silica or more PDMS. One apparent advantage of the soft lithography is that it allows fabrication of multiple replicas of the PDMS chip from a single master mold. Recent advances in soft lithography techniques made the microfluidic technology an ubiquitous tool for biological sciences over the last couple decades. One of the main breakthrough in soft lithography came when Dr. Stephen Quake’s group introduced multi-layer microfluidic chips with unprecedented robustness and design flexibility [94, 95]. At least two master molds are needed to fabricate multilayer microfluidic devices. One of the layers serves as a flow layer and the other as the control layer. For the bottom layer, PDMS elastomer is spin-coated across the mold so a 10-30 µm PDMS layer rests above the photoresist features. After the PDMS of the bottom layer is partially hardened, the top layer of the device, which is typically fabricated as its own single layer in the single microfluidic device fabrication, is bonded to the bottom layer, (see Figure 2.4). The membranes are formed where two layers intersect.
9 Figure 2.4: Fabrication process flow of multilayer soft lithography Two master molds are fabricated using photolithography. One master mold is for replicating the bottom channel (left) on which a thin layer of PDMS is coated by spin-coating. The PDMS replica that was created by the other master mold is orthogonally aligned on master mold coated with the thin PDMS layer, which creates a deflectable thin membrane between the two mold replicas of the channels. The image is adapted from [94]. There are two valve configurations for multilayer microfluidic device fabrication ; push-up and push down [96]. Push-up valves control the flow through a channel from below whereas push-down valves control the flow through a channel from above. Both valve structures use thin deflectable membranes between fabrication layers to control the flow channel (Figure 2.4). With the push-up valve configuration, completely sealed
10 channels can be achieved while push-down configuration can offer only partially sealed channels.
Figure 2.5: Two basic configurations for multi-layer microfluidic valves. a) A PDMS push-down valve, where the control layer is on top of the flow channel with a semi-round cross-section. b) A push-up valve, which has the opposite structure as in part (a). Thin deflectable membranes are used in both cases to close the flow channel [96].
2.5 MICROFLUIDIC DEVICES FOR C. ELEGANS RESEARCH
The conventional worm handling techniques at present include the use of petri dishes or standard multiwell plates [13, 97]. For more precise interrogation and manipulation of the worms, researchers immobilize the nematodes using anesthetics, polystyrene beads or gluing worms to the substrates.
One of the initial examples of microfluidic chips for C. elegans applications was a chemotaxis chip [98]. In this particular study, the authors designed a PDMS device and placed it on an agar surface. The microfluidic chip created an oxygen gradient, which allowed studies of hyperopia avoidance in wild type and mutant worms. In the last decade, there have been several examples of microfluidic platforms for applications such as behavioral studies [31, 33, 36, 98-110], developmental studies [111-117], phenotyping [115, 118-126], and laser surgery [12, 16, 127-130]. 11 In regards to the aim of the dissertation, the discussion will focus on immobilization of living nematodes on microfluidic chips from here on. Nerve regeneration studies in living C. elegans are time consuming and labor intensive since laser axotomy requires complete immobilization of the worm so that the axon of interest can be precisely positioned within the focal volume of the laser beam. In addition, high-resolution imaging of the regenerating axons post injury is necessary, which also requires a high degree of immobilization. Microfluidic immobilization techniques for in vivo studies typically involve mechanical trapping assisted by either a tapered channel, pressurized membranes [12, 13, 16, 128], exposure to a cold (4 °C) fluid to induce temporary paralysis [118], di- electrophoresis [131], or surface acoustic wave manipulation [132]. In one of the first examples of microfluidic surgery platforms, Chung et al. developed a microfluidic platform to ablate cell bodies at a rate of 110 worms per hour [129]. This microfluidic platform constituted three separate layers, including a cold-fluid layer, restriction valve layer, and flow layer (Figure 2.6a). The microfluidic chip employed two worm-loading channels that operate in parallel. This design enabled simultaneous worm-loading and worm-collecting on single chip. The immobilization of L1 stage worms was achieved using temperature-controlled layer. With this layer, the worms in the loading area were exposed to a cold fluid (4˚C) to induce temporary paralysis. After the immobilization of worm was achieved, the ablation of cell bodies was performed by a custom-developed automation program [129]. The most common on-chip immobilization technique for the laser axotomy is the pressurized membranes to exert adequate force for complete immobilization [12, 13, 128]. Guo et al. showed one of the first examples of an on-chip femtosecond laser axotomy platform. The microfluidic platform consisted two positioning channels, one immobilization membrane, and recovery chambers (Figure 2.6b). To immobilize the 12 worms, pressure was applied in the second layer, deforming the membrane above the trapping area. This actuation pushed the worm against the cover glass, allowing an optimum optical access to the neuron of interest [69]. Utilizing the double layer microfluidic platform, researchers observed that regeneration in mechanosensory neurons was much faster when worms were processed on chip, as opposed to those mounted on agar pads with anesthetics [12]. In another attempt towards on-chip femtosecond laser axotomy on a microfluidic platform, researchers developed a semi-automated platform to screen chemical compounds for nerve regeneration studies [16]. In this method, the worms were loaded from multiwell plates tilted at an angle to condense the worms into the corner of each well instead of delivering them via syringe (right panel on Figure 2.6c). With this study, researchers revealed specific chemical modulators of neurite regrowth in the PLM neurons. To summarize, microfluidic platforms for robust and automated on-chip laser axotomy of C. elegans hold great promise to enable high-throughput axotomy assays for nerve regeneration studies. The following two chapters present my effort on the development, testing, and utilization of two comprehensive microfluidic platforms that provide technology that will move researchers closer to this goal.
13 Figure 2.6: Recent examples of microfluidic laser surgery platforms. a)The left panel shows the microfluidic laser ablation platform filled with dye [129]. The active components are: loading channel (yellow), control membrane channel (red), and temperature-control channel (blue). Right panel shows a worm loaded in the loading channel. The image is adapted from [129]. b) The laser axotomy chip for imaging, laser nanoaxotomy [12], and housing of C. elegans. Left panel is an overview of the nano-axotomy platform. View of the trapping system: Valves 1–4 (yellow rectangles) respectively control inlet regulation (1), fine positioning of the worm (2 and 3) and gating to the recovery chambers (4).The right panel shows the conceptual three-dimensional section renderings of the trap channel without and with a worm (green) immobilized by a membrane. The image is adapted from [12]. c) A few worms are delivered to the device, where a single worm is trapped and immobilized for axotomy and imaging after cleaning steps. c) Left panel shows the microfluidic device with key components of the immobilization area filled with different dyes. The syringe-free loading of the worms into the devices was depicted on the left panel.
14 Chapter 3: The Fully Automated Serial Femtosecond Laser Axotomy Chip
This chapter discusses the fully automated serial microfluidic chip to perform femtosecond laser axotomy in C. elegans. The automated microfluidic platform is capable of isolating a single worm at a time from a large population, immobilizing the isolated worm, identifying the location of the worm, detecting the neuron of interest and relative location of axon, and axotomizing the axon in an automated manner. The content of this chapter has been adapted from reference [127].1
3.1 INTRODUCTION
In vivo nerve regeneration studies in living C. elegans are time consuming because the laser axotomy requires complete immobilization of the worm so that the axon of interest can be precisely positioned within the focal volume of the laser beam. In addition, high- resolution imaging of the regenerating axons post injury is necessary, which also requires a high degree of immobilization. The traditional methods to immobilize C. elegans for surgery or imaging include the use of anesthetics [11, 78, 79, 133], gluing worms to substrates [24] or using polystyrene beads [22]. Using anesthetics for immobilization might interfere with the recovery of the worms [134] and, thus, the regeneration process of the injured axons. Gluing methods are not viable methods since the worms cannot be recovered after gluing [24]. Using polystyrene microsphere beads require use of buffer solution exchange to recover the worms, limiting the throughput to around 5-10 worms per experimental set [22, 23]. These limitations of the conventional immobilization methods
1 S. K. Gokce, S. X. Guo, N. Ghorashian, W. N. Everett, T. Jarrell, A. Kottek, A. C. Bovik, and A. Ben-Yakar, "A fully automated microfluidic femtosecond laser axotomy platform for nerve regeneration studies in C. elegans," PLoS ONE, vol. 9, p. e113917, 2014. S.K.Gokce, S. X. Guo, N. Ghorashian, W. N. Everett, and A. Ben-Yakar conceived and designed the experiments. S.K.Gokce performed all experiments. S.K.Gokce and A. Ben-Yakar analyzed the data. S. K. Gokce, S. X. Guo, N. Ghorashian, W. N. Everett, T. Jarrell, A. Kottek, A. C. Bovik, and A. Ben-Yakar contributed to reagents and tools. 15 hinder the throughput of the axotomy processes. To overcome the limitations of manual techniques, new immobilization methods using microfluidic devices have been developed for both imaging [102, 105, 118, 131, 132, 135-138] and surgical studies [12, 16, 128, 129]. Microfluidic immobilization techniques for in vivo studies include, but are not limited to, mechanical trapping assisted by either tapered channels [102, 135, 136, 139], pressurized membranes [12, 16], pressurized membranes with the addition of suction [128], CO2- induced paralysis [13, 116], exposure to cold (4 °C) fluid to induce temporary paralysis [118], dielectrophoresis [131], gel based [140, 141], and surface acoustic wave manipulation [132]. Automation of these microfluidic platforms and the related imaging, and surgery processes is necessary to enable investigation of nerve regeneration in C. elegans at high speeds and with a high-throughput. To achieve full automation of the axotomy process, a serial automated microfluidic platform has been developed and tested, which is presented in this chapter. The full automation was achieved by redesigning our group’s previous microfluidic immobilization method [12] to enable repeatable and rapid immobilization of individual worms. Our group previously demonstrated that a microfluidic immobilization technique based on a deflectable membrane could provide sufficient immobilization to perform precise femtosecond laser axotomy in C. elegans [12]. However, this first device required manual interventions to reduce errors in immobilization orientation and the number of worms trapped at a given time that limited automated identification of the worm body and neurons of interest. To achieve repeatable and rapid laser axotomy of nematodes in a fully automated manner, a new microfluidic was designed using the deflecting membrane immobilization technique. The fully automated serial axotomy platform utilizes novel image processing algorithms to enable the automated ablation of 300 nm-wide axons
16 with a sub-micron resolution. The entire process of staging, trapping, and axotomy requires, on average, about 17 s/worm.
3.2 SYSTEM OVERVIEW
The serial microfluidic chip is designed to perform femtosecond laser axotomies in a fast and controllable manner on single worms without affecting the worm viability and without user intervention during operation. To simplify hardware manipulation and workflow in the optical setup, and to enhance precision of the axotomy process, a single trapping location for optical interrogation was implemented. Unlike most other nerve regeneration studies, this system uses a high-NA oil immersion objective and well-tuned laser parameters to increase axotomy precision, and decrease the variation of regeneration and reconnection results of the highly stochastic axotomy process between each experimental set. As previously shown, the regeneration capability of injured axons directly depends on the precision of laser injury and extent of damage [142]. When the damage to the surrounding tissues is minimized and the axon is severed at a pre-synaptic location, the severed axons could not only regrow, but also reconnect to their distal parts [18, 143, 144] thus restoring at least the neural connectome [11]. Further, high precision requires minimizing the aberrations by directly immobilizing the worms on the cover glass without an intervening layer of PMDS, air, or liquid. Other nerve regeneration studies, that have relied on more relaxed focusing parameters using low-NA air objectives as opposed to functional recovery [16, 145]. To enable high-precision laser axotomies, our group has previously utilized a pressurized membrane to immobilize worms directly against the optical interface for surgery [12]. By eliminating an extra layer of PDMS or dead channel volume between
17 worms and the cover glass, the deflectable membrane technology offered ideal optical focusing and accuracy to study the complete regeneration process [12].
Figure 3.1: Axotomy chip overview. A schematic top-view of the microfluidic chip. The loading chamber is used to house the worms throughout the automation process. The staging area isolates a single worm from the whole population kept in the loading chamber and sends it to the trapping area for immobilization and axotomy. The T-shaped trapping area with a sieve structure enables rapid immobilization of single worms. 3D interconnects enable access to the fully sealing valves to enhance the repeatable localization of worms against the sieve structure in the trapping area by completely stopping the flow to the exit outlets. After each axotomy, the flushing inlet guides the flow to take the worm through one of the outlets. In this current serial microfluidic design, the chip was redesigned into a unique configuration to enable its full automation along with adopting the same immobilization methodology as previously utilized [12]. The new serial microfluidic chip contains five distinct compartments (Figure 3.1): (1) a loading chamber to house a population of up to 250 worms, (2) a staging area to isolate a single worm from the population in the loading chamber and delivering it to the trapping area, (3) a trapping area to ensure repeatable and rapid immobilization of single worms near the focused laser beam, (4) 3D 18 interconnects to enable transition to completely sealing valves, and (5) flush exit outlets to transition processed worms to an off-chip location. In the following sections, the details of the serial microfluidic chip and unique characteristics of the microfluidic platform are presented. Then, the automation sequence including both automated actuation of valves and on-chip flow; as well as image processing methodology are discussed.
3.3 MICROFLUIDIC DEVICE DESIGN
A key design consideration when developing the automation program to perform femtosecond laser axotomies in C. elegans is the optimization of single worm delivery from a pre-loaded population into the trapping area while minimizing the degree of spatial variability in the trapped position of the worm. More specifically, the ability of trapping a single worm at the same location is essential to have a high success rate of the automation process. To reduce ambiguity in axonal reconnection data, other design considerations include overcoming delivery challenges such as trapping a worm in a folded configuration (Figure 3.2a), multiple worms in the trapping area (Figure 3.2b), and sending a non- axotomized worm into the pool of axotomized worms. With these challenges in mind, the serial microfluidic chip has three new components: 1) a staging area to isolate individual worms from preloaded population, 2) a T-shaped configured trapping area for fast and repeatable worm trapping, and 3) 3D interconnects to incorporate fully sealing valves.
19 Figure 3.2: Worm delivery challenges in the trapping area a) The undesired orientation of the worm inside the trapping area, which was overcome by actuating the trapping membrane, valve V3, in a cyclical manner during the initial trapping procedure while being pushed by the flow from the staging area. b) The microphotograph shows an example of multiple worms injected to the trapping area. Only one of the worms (left) was immobilized. The other one (right) was partially immobilized. Only tail part of the left worm was underneath the pressurized trapping membrane. Staging area: In the co-linear configuration of our previous design [12] , it was observed that transporting the worms at very high speeds to the trapping area, would occasionally result in multiple worms being trapped or some worms being lost when removing an axotomized worm. To isolate a single worm from a pre-loaded population of worms and avoid trapping of multiple worms, a staging area is placed before the trapping area. The new staging area incorporates two partially sealing gate valves (V1, V2) separated by a narrow channel that allows for the containment of only one Larval 4 (L4)
20 stage worm and prevents other worms in the main chamber from entering (Figure 3.3a). The main staging channel is 30 µm × 35 µm with a length of 600 µm, which is the approximate dimensions of an L4-stage worm [146]. It was previously shown by our group that a deflected PDMS membrane could almost completely seal a 30 µm-deep, 120 µm- wide rectangular channel, leaving small gaps in the bottom corners of the channel [12]. Accordingly, the staging channel beneath the gate valves (V1, V2) was designed to be 120 µm wide to prohibit staged or non-staged worms from passing through the actuated valves. T-shaped configured trapping area: The new T-shaped trapping area design enables the automated delivery and trapping of single worms in the desired location (Figure 3.3a). Automatic identification of the neuron of interest in the trapped worm requires processing of high-resolution images within a small field of view (FOV). It is therefore important to immobilize the worm in a location close to the desired FOV to find the neuron rapidly using a single step image acquisition. In the co-linear trap design, positioning the worm underneath the trapping membrane was extremely difficult, hindering the throughput of the axotomy assays [12]. To overcome this problem, our research group and other research groups incorporated complex manipulation methods for fine-positioning of the worms using, for example, side channels [12, 16]. However, such complex manipulations required manual operation interventions. The proposed T-shaped channel configuration of the trapping area eliminates the need for such complex manipulations by providing two major advantages. First, the structure provides a repeatable immobilization location by injecting the worm close to the middle of the sieve structure. Second, the channel shape allows for perpendicular decoupling of the injection and flushing channels, which permits a reliable and straightforward worm ejection after axotomy. A worm’s entire body is pushed against an array of short and narrow flow outlets that form the microfluidic sieve structure (Figure 3.3b). The pressure drop across these channels immediately straightens 21 the delivered worm into an elongated body position just before actuation of the trapping membrane. 3D interconnects: Microfluidic valves actuated in channels with rectangular cross- sections do not block the channel flow completely, even at very high valve pressures. While the staging area configuration took advantage of the leaky nature of these valves, such structures downstream from the trapping area resulted in inconsistent positioning of worms during immobilization. Worms delivered to the center of the trapping area showed less motility than the ones immobilized around the corners of the trapping area. The bending membrane of the trapping area restricts the worm’s whole-body better at the center of the trapping area. This step is critical for minimizing worm motility due to pharyngeal pumping and led to an improvement in ablation accuracy. This type of positioning error could be overcome with valves that completely sealed the exit flow channels. Valves actuated in channels with hemispherical cross-sections have been known to seal completely. However their fabrication would necessitate a thin layer of PDMS [118, 129] or a control layer between the worm and the cover glass in the trapping area [147]. The presence of this additional PDMS layer in the optical path would introduce an index of refraction mismatch and spherical aberrations at focusing distances beyond 30 – 40 µm, reducing the system’s effective NA and compromising the precision of both imaging and surgery. To avoid the additional PDMS layer, the fluid flow was diverted to another microfluidic flow layer and both flow layers were connected using new 3D interconnects. Interconnects were created on both sides of the trapping area by punching thru-holes at overlapping microfluidic structures within the first and second layers, as show in Figure 3.3c. To prevent media from flowing out of the device from the punched thru-hole, a permanent metallic plug (Figure 3.3c) was inserted into the thru-hole at a depth that it did not interfere with flow within the interconnect. Fabricating the fully sealing valves in a 22 different layer than the axotomy layer and connecting them with a permanent 3D interconnect, eliminated optical distortion and degradation of the image and ablation quality of the system. These three features simplified the image processing-based approach to identify anatomical features of the worm and speed up the process of automated analysis.
23
Figure 3.3: Flow direction in T-shaped staging/trapping area and 3D interconnects. (a) Optical image of a dye-filled microfluidic device with black arrows indicating the direction of fluid flow. Orange dye fills the control layer and the blue dye identifies the flow channels. The loading chamber holds pre-loaded worms before their serial transportation into the staging area. The synchronized actuation of valves V1 and V2 in the staging area allows loading of a single worm against the microfluidic sieve in the immobilization zone. A partially sealing trapping membrane, actuated by valve V3 in the control layer, then physically immobilizes the worm for laser axotomy. (b) Schematic cross-section referring to the sectioning arrows A-A' in (a) that shows the flow direction through the sieves during membrane deflection, location of the worm in the trapping area during delivery and after membrane deflection, and the relative heights of the microfluidic sieve and channel within the immobilization zone. The objective is placed underneath the glass interface. Avoiding any additional PDMS layers in the optical pathway eliminates optical distortion for imaging and ablation. (c) Top view and cross-sectional view (y- y') of a 3D interconnect that enables transitioning the flow from the 1st layer (controlled by partially sealing valves) into the 2nd layer controlled by completely sealing valves. A metallic pin (red) is plugged half-way into the through hole that connects the layers. The cross-sectional view of a partially sealing valve is given along x-x' while a completely sealing valve is shown along z-z'.
24 The final design consideration is related to the capture of un-wanted debris during device operation. Despite efforts to remove particulate matter from the worm suspension in M9 buffer prior to loading worms into the device, there was still an accumulation of microscopic particles within the chip during the automated process. To prevent the sieve structures from clogging in the staging and trapping areas, which could negatively affect chip performance and could eventually lead to total chip failure, an array of staggered filter structures with gaps ranging from 10 µm down to 5 µm at the entrance of each flow channel were built [148]. Additionally, an array of pillars spaced 30 µm apart were fabricated. The array of pillars allowed for the passage of worms into the loading chamber, but blocked a large fraction of debris from entering the trapping area and clogging the sieve structures in the staging and trapping areas.
3.4 PROGRESSION OF VALVE ACTUATION, FLOW, AND WORM MANIPULATION PROCESSING
The automation software, developed on a LabVIEW platform, controls the external solenoid valves maintaining flow into the device and the on-chip valves to synchronize the automation steps. Specifically, it stages worms for serial processing, traps them individually for laser surgery, and controls the remainder of flow throughout the device. While the worm is immobilized in the trapping area, femtosecond laser axotomies are carried out on immobilized worms by the custom-developed automation software (details of the automation program are given in the next section). For the entire duration of
25 automated operation, a constant head pressure of ~15 kPa is used to continually drive flow through the loading chamber and move worms into the staging area.
Figure 3.4: Automated progression of valve actuation and flow. (a) A schematic representation of the chip, showing the valves, channels, and chambers/areas indicated by their reference numbers. Valves V1 and V2 are used to stage and inject individual worms serially into the trapping area (4). Valve V3 serves as the immobilizing membrane. Valves V4 and V5 are used to open and close the ejection and flush channels, respectively. The ejection channel is used to deliver worms that have been successfully axotomized to a recovery area, and the flush channel is used to jettison worms that failed at any step of the automation process. Two-way flow through the side channels (3) in the staging area aid in serial staging and injection of worms into the trapping area. A two-way channel (5) in the trapping area (4) allows the flow through the microfluidic sieve structure to push the worm against the sieve structure during loading and away from the sieve structure during unloading of the worm along with the one-way side channel (6) leading to the trapping area. (b) Filling the loading chamber (2) with a population of worms by opening side channels (1) and closing all other valves and channels. (c) Staging of a single worm by opening valve V1, closing valve V2, and pushing the worm into the staging channel where flow is directed out through the side channels (3). (d) Preventing additional worms from entering the staging area by closing valve V1. (e) Injecting the worm into the trapping area by opening valves V2 and V3 and reversing the flow in the staging side channels (3). Valve V1 is also opened to prevent other worms from entering the staging area prematurely. (f) Immobilizing the worm by closing valve V3 in a cyclical pumping manner and then performing automated axotomy on the trapped worm using image- processing algorithms. (g) Transporting the successfully axotomized worm into the recovery area through the ejection channel (7). (h) Starting the next cycle by loading the next worm in the staging area. The sequence of valve and flow progression at each step during automation is shown in Figure 3.4. The numbering of valves and chambers/channels is provided in Figure 3.4a. First, a population of worms is loaded into the device by blocking all flow channels
26 except the small flow exits (1) in the side of the loading chamber (2) (Figure 3.4b). After the loading chamber has been filled with worms, the gate in the staging area is used to withdraw a single worm and inject it into the trapping area by opening and closing the two valves located at the front (V1) and back (V2) of the staging zone (see Figures. 3.4c –d). An array of small channels (3) on both sides of the staging channel acts as a sieve-like fluidic path to direct the worm between valves V1 and V2 during staging. Once a worm is located and isolated from the rest of the population in the staging area, it is injected into the trapping area (4) by reversing the flow through the staging sieve with a head pressure of ~65 kPa (back into the staging channel and opening valves V1, V2, and V3 for 1000–1200 ms (Figure 3.4e). This valve sequence pushes the worm against the sieve (5) in the trapping area, preparing it for trapping and surgery. Reversing flow in the staging sieve and opening valve V1 during this injection period also helps to prevent worms within the loading chamber from prematurely entering the staging area. During the trapping phase, valve V3 is actuated in a cyclical manner (close, open, and close) to avoid unfavorable worm folding (Figure 3.2) as the membrane begins to immobilize the worm. Immediately after immobilizing the loaded worm and recognizing its body centroid via image processing algorithms, the system moves the translation stage automatically to align the center of the worm body within the center of the FOV. After switching the objective from 5× to 63×, the automation program proceeds with positioning the laser beam on the axon of interest automatically (Figure 3.4f). Details of the image processing algorithm and axon ablation are described in the following sections. After performing the axotomy, the system switches back to the 5× objective (large FOV) and the software simultaneously opens valves V3 and either V4 (flush) or V5 (ejection) (Figure 3.4g). The automation software makes an intelligent decision as to whether or not the outcome of each individual automation step during trapping and 27 axotomy is successful. If the outcome is negative, the corresponding worm is flushed through the waste channel immediately after the unsuccessful step. Successfully axotomized worms are collected through the ejection channel. An external solenoid valve is simultaneously actuated to reverse flow through the sieve structure in the trapping area and to deliver fluid through the one-way-flow flush channel, both with a head pressure of ~135 kPa. After the valve sequence rapidly removes the worm from the trapping area and delivers it through either the flush or the ejection channel, the next cycle starts with staging the another worm from the pre-loaded population in the housing chamber (Figure 3.4h, just as in Figure 3.4c). This automated process is repeated until axotomies are performed on the desired number of worms from the loaded sample population, and any remaining worms are then removed from the chip by opening all on-chip valves and reversing the flow through the sieve structure in the trapping area. The entire process of staging, trapping, and axotomy requires, on average, about 17 s/worm.
3.5 IMAGE PROCESSING METHODOLOGY FOR AUTOMATED IDENTIFICATION OF NEURONS AND TARGETING FOR LASER AXOTOMY
Soft touch is sensed by six touch receptor neurons, which are the anterior lateral microtubule (ALM) pair, anterior ventral microtubule (AVM), the posterior lateral microtubule (PLM) pair, and posterior ventral microtubule (PVM),(see Figure 3.5) [149,
150]. Half of these neurons respond to gentle touch in the anterior part and the other half neurons are responsible for the gentle touch in the posterior half of the body. A pair of these neurons (the ALM pair) runs anteriorly along both sides of the worm with the somas located close to the worm’s centroid. The custom image processing methodology was developed to perform axotomies automatically on GFP-labeled mechanosensory ALM neurons.
28
Figure 3.5: The soft touch neurons of C. elegans: Left lateral view (a) and ventral view (b) of fluorescent images of an adult hermaphrodite C. elegans expressing green fluorescent protein (GFP) in six touch receptor neurons. The image is adapted from [151]. c) Top schematic shows approximate locations of six touch receptor neurons (TRN). The axes legend refers to ventral, posterior, anterior, and dorsal directions. The bottom shows the cross-sectional view of the worm body. The image is adapted from [103]. The automation software uses a four-step image processing procedure to automatically identify the neuron, locate the target on the desired axon, and perform laser axotomy for injury. The software is also able to detect and flush away worms that are not immobilized in a way that allows the image processing algorithms to pursue a successful axotomy. A flow chart describing the whole automation process, including image- processing steps, is given in Figure 3.6. It is important to note that Step 1 in the flow chart involves all the valve actuation steps to trap a single worm, including staging, injection and
29 trapping, in addition to the image processing step that are discussed in the following sections.
Figure 3.6: Automation Flowchart. Flow chart illustrates the steps of the automation process, including the image processing algorithms used to find and ablate the axon of interest.
30 3.5.1 Step 1: Identification of the worm location
Once a worm is immobilized, which can occur anywhere within the trapping area (Figure 3.7a), it is necessary to identify the relative location of the centroid of the trapped worm. The knowledge of the centroid location helps to verify the worm location immobilized under the deflected membrane/in the trapping area, and provides valuable information on the relative location of the neuron of interest (ALM for this work). The stereotyped neuroanatomy of C. elegans enables accurately positioning of the high- magnification, small FOV near the desired neuron for the subsequent automation steps, where fine focusing of the target axon and ablation occurs. By processing the low- magnification (5×), bright-field images of the trapping area, the software finds the relative location of the worm within the trapping area. The image processing involves background subtraction and thresholding. Before trapping a worm, the software saves a baseline image of the similar FOV without a worm but with the pressurized trapping membrane (Figure 3.7b). By subtracting the baseline image from the snapshot of the trapped worm, the background is removed and only the worm remains in the resultant image (Figure 3.7c). The program next extracts a pre-defined region of interest (ROI) from the resultant image, based on the perimeter of the trapping area. An image-thresholding filter is applied to enhance contrast (Figure 3.7d). To eliminate noise in the processed image, a particle filter removes all features spanning areas smaller than 300 pixels. If the detected center of the worm is found near the edge of the ROI, the trapped worm is flushed (rejected) and the
31 software proceeds with staging the next worm. This simple subtraction algorithm eliminates the need for complex and time-consuming pattern recognition algorithms.
Figure 3.7: Image processing methodology for identifying the worm location within the trapping area (Step 1). (a) Bright-field image of an immobilized worm. (b) Background image of the trapping area with the same FOV as shown in (a) with the trapping membrane fully actuated. The image in (b) is then subtracted from the image in (a), resulting in the image given in (c). (d) Image thresholding and noise filtering is then used to generate a high degree of contrast so that the centroid of the worm can be accurately located.
32 3.5.2 Step 2: Detection of a neuronal cell body in the small FOV
After the centroid of the trapped worm is defined and translated into the center of the FOV, the 63× objective lens moves into place and the illumination is switched to fluorescence mode. Here, finding the centroid of the worm in Step 1 ensures that there are only ALM and possibly AVM neurons present in the small FOV. Other anatomical features need to be integrated to perform axotomies on other neurons such as the PLM. To find a cell body in the small FOV, the coarse z-stage then begins to advance the focal plane in steps of 2.5 µm into the body of the worm (Figure 3.8a), collecting fluorescent images at each increment and looking for circular features. Each step moves the focal plane towards either the left or right ALM neuron, reaching to a neuron positioned closest to the cover glass-worm interface, and until a circular shape corresponding to the soma is detected. It is important to note that when perform surgeries are carried out on ALMs, no distinction is made between the left and right ALM (Figure 3.9a). To find a cell body, images collected at each z-step are thresholded to a pre-determined intensity cutoff (determined empirically to be 8× the mean intensity) until a circular feature drops to a radius between 2 and 6 µm (Figure 3.8a). If the program cannot detect a circular feature in more than 10 iterations, it flushes the trapped worm and proceeds to stage the next worm. This cell body-locating process provides a fast method to find the neuron soma and adequately brings it closer to the focal plane, avoiding the need for slower fine-focusing approaches with higher resolution capabilities that are unnecessary at this stage of the automation program.
33 Figure 3.8: The circular object detection methodology to detect a cell body in the field of view (Step 2). (a) Fluorescence image of the detected cell body in the 63× FOV. (b) Thresholded image of the fluorescent cell body in the 63× FOV. In the thresholded fluorescence images, the automation program looks for objects with circular shapes having diameters between 2 µm (red circle) to 6 µm (dashed circle). The white object shows the detected cell body that is a little larger than the lower limit of desired size of the cell body. (c) The fluorescence image of the cell body is relocated to the location of the laser spot, which is close to the center of the FOV to aid in further image processing.
34 3.5.3 Step 3: Verification of neuron of interest
The next step in the automation is the verification of the neuron of interest and the axon’s orientation relative to the anterior/posterior body axis of the worm. By fine-focusing on the cell body and looking for axonal processes, the program determines if the detected cell body is the neuron of interest and finds its orientation. For fine-focusing, a z-stack of images (0.7 µm steps) is collected via piezoelectric actuator translation (Figure 3.9). The image with the highest variance of pixel intensity correlates to the most in-focus z-position
[152, 153]. The variance of intensity in each frame ( ) is calculated by: = ∑ ∑ − ̅ , (1)
where Iij is the intensity of a single pixel in the image and ̅ is the average pixel intensity of an image with an M×N array of pixels. Before the variance of intensity of each frame is calculated, a 2D Laplacian of Gaussian (LoG) bandpass filter [154] is convolved with each image to simultaneously reduce high-frequency noise and enhance the intensity of the axon. The LoG-filtered image is given as:
( , ) = ∇ ( , ) ∗ ( , ) , (2) where ( ) ∇ ( , ) = , (3)
f 0 (x, y ) is the original unfiltered image, and σ is assigned a value of 2. After the best focus is achieved, the automation program creates two small rectangular ROIs (150 × 200 pixels) on the left- and right-hand sides of the cell body to determine if an axon is in the form of a straight feature within each ROI (Figure 3.10d). The existence of such a feature distinguishes the ALM neuron from the AVM neuron, which is the only other possible neuron expressing GFP within the small FOV based on the known neuroanatomy and the GFP promoter used in our strain. The detection of an axon also determines the orientation of the worm’s head and tail (Figure 3.10a); ALM neurons extend their axonal 35 process in the anterior direction. In some cases, however, they also have a minor neurite extending towards the tail. In these cases, the brightest axonal process usually indicates the axon of interest extending towards the head. If the program cannot identify straight edges in either side of the neuronal soma, it decides that the cell body is not the neuron of interest and flushes the trapped worm and proceeds to staging a new worm.
Figure 3.9: Fine focusing methodology to verify the neuron of interest and determine the orientation of the axon. The stack of images on the left was obtained during fine focusing using the piezoelectric actuator with a step size of 0.7 µm. The desired focal plane is determined by finding the image with the highest variance in pixel intensity. Two selected images from this stack are shown separately, one in focus (top right) and one out of focus (bottom right) to show different degrees of focus. The neuron with an axon extending from its side can be identified as the ALMR neuron and the neuron without any axon can be identified as the AVM neuron following the neural anatomy of C. elegans.
36
Figure 3.10: Image processing steps to verify the neuron of interest (Step 3), locate the target on the desired axon, and perform laser axotomy (Step 4). (a) A schematic of C. elegans, showing the relative anatomical locations of the neuron of interest (i.e., ALML and ALMR). (b) Automation software finds the centroid of the worm and moves the focus proximal to the glass/worm interface at position (x1, y1, z1), as described in Step 1, and then locates a cell body using coarse focusing with the motorized stage to (x1, y1, z2). (c) After finding cell bodies in the FOV, the program brings a cell body near the laser spot at (x2, y2, z2). (d) The resultant z-location after performing fine-focusing on the detected cell body. To determine the relative location of the axon and distinguish the ALM neuron from the AVM neuron, as described in Step 3, the programs looks for straight edges in two small ROIs on the sides of the cell body. (e,f) After determining the orientation of the worm, the translation stage moves along the axon to (x3,y2,z3) and performs a quick focusing procedure on the axon at (x3,y2,z4) to obtain the best focus. (g) The piezo stage finally translates the axon to the laser spot location along the y-axis to position (x3,y3,z4) and performs laser axotomy. The insert shows a magnified view of the cut axon just after the ablation. (h) Graphs of the lateral (top) and axial (bottom) positions of the neuron of interest during the overall image analysis part of the automated axotomy process in the small FOV.
37 3.5.4 Step 4: Laser axotomy
After verifying that the cell body belongs to the neuron of interest and determining the axon location, the translation stage moves 50 µm from the soma towards the head of the nematode (Figure 3.10e). Then the automation program performs another fine focusing step to locate the axon within the focal volume of the laser beam along the z-direction (Figure 3.10f). In a manner different from the previous fine focusing step, a direct comparison of mean pixel intensities of the regions near the axonal branch is used to find the best z-location. In the final step before axon ablation, the piezoelectric actuator moves precisely in the y-direction to align the laser spot with the axon. Given that the diameter of the axons of interest is ~300 nm, their precise ablation with a laser beam focused to a 1/e2 diameter ablation spot of ~620 nm requires high-precision alignment. With the 63× objective, these dimensions correspond to three and seven pixels respectively, giving a positioning tolerance for axotomy of only one pixel on either side of the axon to ensure a proper cut mainly with the center of the beam. Due to the positioning hysteresis of the piezoelectric actuators, we incorporated a closed-loop proportional control algorithm based on imaging feedback to drive the actuators to find the sub-pixel center of the axon in the y-axis. The distance (in pixels) between the axon's center and the ablation target serves as the iterative error in the control algorithm, thereby determining the distance that the piezoelectric actuator needs to be translated. The process is repeated until the axon is positioned within ~1 pixel from the ablation target (Figure 3.10g). If the program cannot achieve this goal in 10 iterations, it flushes the worm and proceeds with staging the next worm. Spatiotemporal plots of the target location on the neuron of interest relative to the focal point of the laser beam during the small FOV (63×) automated processing step, are given in Figure 6h.
38 3.6 CHARACTERIZATION OF THE AUTOMATED PLATFORM
3.6.1 Effect of chip manipulation on worm survivability
To determine the effect of on-chip immobilization on worm survivability, a population of 20 worms was performed without performing axotomies, using a full cycle of valve actuation (as described in Figure 3.4), and immobilizing each worm for 30 s with a trap pressure of 155 kPa. Control and trial groups underwent the same synchronization and cleaning procedures. Control group did not go through any process in the microfluidic chip. The trapped worms were collected on NGMSR (Streptomycin-Resistant Nematode Growth Medium) plates. The viability of the worms was checked in each population every 24 hours and worms were transferred to new NGMSR plates whenever necessary. We used the Log-Rank test to determine the difference in the viability between groups. The average lifespan of the immobilized population was found to be 17.6 ± 4.2 days, whereas worms in the control group lived for an average of 19.3 ± 3.3 days. No statistically significant (p=0.14) difference in outcome was identified for the two groups (Figure 3.11).
39 Figure 3.11: Lifespan analysis. The viability of worms immobilized inside the serial microfluidic chip with an applied trapping pressure of 155 kPa for 30 seconds (blue) as compared to the control group (orange). (Log-Rank test, p=0.14).
3.6.2 Timing and axotomy success rates
The success rate was found to be 67.6 ± 3.2% (mean ± SEM) from four separate sets of axotomy experiments, namely 236 successful axotomies among 350 processed worms (Figure 3.12). The time required for each individual step in the process was recorded using the custom-written automation software (see Figure 3.13). The average timing values for each step are given in Figure 3.13a. The timings of each step are presented for each individual experiment in Figure 3.13b. One of the main reasons for the variability in each step’s timing were due to variation in the relative location of the neuron of interest to the cover-glass (in the z-direction) and variation of the orientation of each trapped worm (in the x- and y-directions). The percentages along the top of Figure 3.13a indicate the remaining population after each step of automation.
40
Figure 3.12: Average process timings per worm for different experiments Four separate sets of automation experiments were performed. Axons were severed successfully in 67.6 ± 3.2% of the cases (n=350). Actual number of processed worms and successfully severed worms are given inside each bar. Average full cycle process time for each set of experiments is given below the each bar in parenthesis. Step 1 in the automation process was found to be the second longest step (4.8 s) of the full cycle after Step 4. This step includes staging, injecting, and immobilizing the worm, along with carrying out image processing algorithms to calculate the relative location of the worm. Approximately 10% of the population was flushed through the waste outlet in Step 1 due to either the appearance of bubbles in the trapping area or the presence of multiple worms in the imaging area. Coarse focusing (Step 2) step took approximately 3.5 s with a rejection percentage of 10%. The main reason for rejection was the difficulty in detecting a cell body in the
41 coarse focusing procedure. As the translation stage moved towards the cell body to identify a circular shaped object, because of the coarse steps, the stage would sometimes pass beyond the cell body in between the steps and miss locating a cell body in the FOV. This step also showed a high variation in timing because of the variation of the variation of the cell body location with respect to initial positioning of the stage (Figure 3.13b). This step was very effective in coarsely locating the cell body quickly after switching from low NA to high NA imaging. Step 3 resulted in flushing a moderate number of worms (9.1%) when the edge detection could not verify the neuron of interest due to a weak axonal signal in most of these cases. The longest step was Step 4 (5.7 ± 2.1 s) to enable precise laser axotomy that required performing time-consuming fine-focusing process on the axon and high- resolution alignment of the laser spot with the axon along the y-axis. While Step 4 was the longest one, it was the step with the highest success rate. Only a small number of worms (3.5%) did not go through a successful ablation in this last step. If the system could not move the axon sufficiently close to the focal plane in the z-axis based on the pre-defined number of iterations and stage adjustment ranges, the system would be unable to find the axon target along the y-axis due to the out-of-focus background signal. The high variation of timing for the laser spot alignment could be mainly related to the inherent hysteresis of the open-loop piezo actuator while positioning the laser spot with respect to the axon. This issue can easily be overcome by replacing the actuator with strain-gauge based controllers.
42 The second minor issue was related to the variation in the background signals and/or morphological differences among worms.
Figure 3.13: Success rate and timing performance of the automation. a) The average times required to perform a successful automated axotomy in single neuron per worm for each individual step of the automation process are indicated with colored bars. The accompanying error bars indicate the standard deviations measured from two different sets of experiments with a total number of successfully axotomized worms of n=236. The average percentages of worms remaining (from all the processed worms, n=350) after each step is given above each corresponding time bar at the top of the figure. b) Timing of automation steps for each successful trapping experiment (n=236). Worm labeling remain consistent through all graphs.
43 The average automation time to execute the complete process for each worm was found to be 17.0 ± 2.4 s/worm among the n=236 successful axotomies obtained in four separate runs (Figure 3.12).
3.6.3 Automated on-chip surgery axonal reconnection rates
To determine axonal reconnection rates following on-chip laser axotomies, the axotomized worms were collected on freshly seeded agar plates and imaged the axotomy site for signs of regrowth and reconnection after 24 h of post-surgical recovery at 16.5 °C (Figure 3.14). The main interest was to understand whether there was successful reconnections in the ALM neurons after automated on-chip axotomies and compare them to the results obtained by manual ablation on agar pads. Two primary criteria were used to describe robust reconnection: (1) proximal re-growth trajectories intersecting the distal axon and (2) a lack of beading or fragmentation in the distal axon that normally marks the beginning of Wallerian degeneration [18, 143]. For example, Figure 3.14a shows a fluorescence image of an injured axon reconnecting successfully to its distal end. Whereas regrowth with a lack of reconnection is evident by a dimmed GFP signal and by beading in the distal part of the axon (Figure 3.14b).
44
Figure 3.14: Imaging of regrowing axons of interest 24 hours after surgery. a) Images at three different z-locations showing an example of reconnection with the connection point of distal and proximal ends indicated by the arrow. b) Images at three different focal planes showing regrowth with a lack of reconnection, as evidenced by the severed ends taking paths in different focal planes. The fragmentation and beading in the distal part shows the lack of reconnection. There was no found statistically significant difference for reconnection probabilities between two different laser ablation methods under two conditions (Figure 3.15). For the first ablation condition, a train of 300 laser pulses with a pulse energy of 4 nJ and pulse-width of 110 fs was used, whereas for the second condition a train of 300 pulses each having an energy of 7.5 nJ and pulse-width of 260 fs was used. For the first ablation condition, the percentage of neurons that exhibited reconnection after anesthetized ablation was 58/111=52%, whereas the on-chip ablation resulted in a reconnection percentage of 46/101=46% (p=0.34, Fisher’s Exact Test). For the second ablation condition, the percentage of neurons that exhibited reconnection after anesthetized ablation
45 was 28/41=68%, whereas the on-chip ablation resulted in a reconnection percentage of 45/67=67% (p=1.00, Fisher’s Exact Test).
Figure 3.15: Axonal reconnection results. Axonal reconnection rates of the ALM neuron for two different laser conditions (300 pulses of 4 nJ pulse energy, 110 fs pulse-width and 300 pulses of 7.5 nJ pulse energy, 260 fs pulse width). The results show no statistically significant differences between automated axotomies on the chip and axotomies performed on agar pads using anesthetics. The numbers of reconnected neurons are given inside each bar. Statistical significance is determined using Fisher’s exact test: p ≥ 0.05 in both cases.
3.7 EXPERIMENTAL PROCEDURES
3.7.1 Device fabrication methods
Standard soft-lithography techniques, with some modifications, were used to fabricate the two-layer microfluidic device described here [155]. The bottom layer that transports the C. elegans is hereafter termed the "flow layer and the top layer that both immobilizes the worms and actuates the valve structures on the chip when pressurized will be referred to as the "control layer.” Photoresist patterns, produced using Mylar masks
46 (CAD/Art Services), were used to create the molds for all polydimethylsiloxane (PDMS; Sylgard 184, Dow Corning Corp) microfluidic structures. To begin, the first step was patterning of the sieve structures by spin-coating SU-8 3005 onto a 4" silicon wafer to a thickness of 8-10 µm. The sieve structures are the arrays of short flow outlets located in the trapping, loading, and staging areas shown in Figure 1. Then, SU-8 2025 atop the sieve structures at a thickness of 30 – 35 µm was coated and created the remainder of the flow layer mold by alignment and exposure through a second photomask using a mask aligner (MA6/BA6, Suss MicroTec). The mold for the control layer was fabricated with combined patterns of a positive resist (AZ 50XT, Applied Electronic Materials) and a negative resist (SU-8 2025) [121]. Reflow of the positive resist at 125 ˚C for 4 min was performed to create semi-circular channel cross-sections. The wafers with the developed SU-8 molds were modified with a fluorinated silane (SIT8173.0, Gelest Inc.) that served as a release agent. All resist film thicknesses were verified with a stylus profilometer (Dektak 6M,
Veeco). Fabrication of control layer PDMS involved the following steps: 1) Thoroughly mixing of the resin with the crosslinker at a ratio of 10:1 (resin:crosslinker), 2) degassing the mixture in a vacuum chamber at room temperature, 3) pouring the degassed mixture onto the control layer mold to a thickness of ~5 mm, 4) degassing again, and finally, 5) curing at 75 °C in an oven for 30 min. Creation of the flow layer involved spin-coating PDMS onto the flow layer mold at 1700 rpm for 33 s and allowing it to rest at room temperature for 5 min. This process resulted in a uniform ~50 µm-thick PDMS flow layer and an approximately 20 µm-thick PDMS membrane covering the top of the SU-8 features. The PDMS on the flow layer mold was then partially cured on a hot plate at 70 °C for approximately 10 min. The thick control layer was aligned and bonded on top of the partially cured flow layer mold with the aid of a stereoscope. To 47 improve the bonding strength between the two PDMS layers, the wafer was placed in an oven at 65 °C overnight. After peeling the two-layer PDMS device from the mold, we punched holes through the PDMS at the inlets and outlets to make external fluidic connections. The device was then bonded to a 25×50 mm #1.5 cover slip using an oxygen plasma treatment and then placed in an oven at 65 °C for 4 h to enhance the PDMS-glass bonding. Sterile polyethylene tubing (Intramedic) was connected to the device using 22 ga. stainless steel couplers (Instech Solomon) inserted into the punched PDMS holes.
3.7.2 Opto-mechanical setup
The laser axotomy setup incorporates custom optics to deliver femtosecond laser pulses for surgery into a home-built epi-fluorescence microscope (Figure 3.16) [12]. We carried out axotomies using a train of femtosecond laser pulses at a center wavelength of 802 nm generated at a repetition rate of 1 kHz (Spitfire, Spectra Physics). The beam energy was measured with an energy meter (PJ10, Ophir) prior to performing all axotomies and adjusted with two sets of half wave plates/cube beam-splitters pairs. An objective lens with a high numerical aperture (NA=1.4) tightly focused the laser beam to an estimated 1/e2 spot size of 620 nm [142]. Automated microscopy was performed with a 5× air objective (Plan-Apochromat, NA=0.16, Zeiss) and a 63× oil-immersion objective (Plan-Apochromat, 63×, NA=1.4,
Zeiss). For fluorescence imaging of green fluorescence protein (GFP) labeled axons, a mercury arc lamp (XCite 120, EXFO) provided the excitation light source passing through a FITC filter set (Semrock). A three-axis translation stage made of individual actuators (LTA-HS, Newport) and operated by a single controller (ESP301-3, Newport) positioned the samples. These stages could translate at up to 5 mm/s with a minimal incremental motion of 100 nm and a lateral resolution of 35 nm (achieved after backlash compensation).
48 High precision positioning was performed by a three-axis piezoelectric actuator (MAX 302, Thorlabs) with a minimal theoretical step size of 25 nm and a travel range of ±10 µm for each axis. A CCD camera (1392 × 1040 pixels with 6.45 µm pixel size, CoolSnap ES, Photometrics) captured the images with fields of view (FOV) of 1.8 × 1.34 mm2 at 5× magnification (1.29 µm/pixel, 1.88 µm resolution at 500 nm) and 143 × 107 µm2 at 63× magnification with 1.4 NA (102 nm/pixel, 214 nm resolution at 500 nm). For controlling the device flow layer, pressurized external fluid chambers controlled by three-way solenoid valves (Lee Company, LHDA0521111H, respectively) were coupled to the chip via a manifold (LFMX0510418). These chambers contained M9 buffer solution (22 mM KH2PO4, 22 mM Na2HPO4, 85 mM NaCl, 1 mM MgSO4, in dH2O). To minimize debris, all M9 buffer was passed through 1.2 µm in-line filters (Acrodisc, Pall Corp.) prior to entering the microfluidic device. Valves were independently actuated with a multichannel amplifier (Automate Scientific) that was controlled with a DAQ card
(USB6501, National Instruments). All automation steps, including stage positioning, valve actuation, and image processing, were performed with a custom-written LabVIEW (National Instruments) program.
49 Figure 3.16: Schematic of the serial automated laser axotomy setup. The GFP-labeled neurons of the worms are excited by a mercury arc lamp (blue lines) and imaged by a high-NA objective lens onto a CCD camera (green lines). The surgery pulses are delivered to the sample through the same objective lens after being attenuated (red lines). Legend: SH – shutter, ATR – attenuator, FL – femtosecond laser, ML – mercury lamp, MR – mirror, DM – dichroic mirror, WL – white light source.
3.7.3 C. elegans maintenance
C. elegans were maintained at 16.5 °C on NGMSR (Streptomycin-Resistant Nematode Growth Medium) agar plates seeded with HB101 E. coli bacterial culture using standard procedures [156]. We studied the regeneration (axonal regrowth and reconnection to their distal ends) on one of the touch receptor neurons – the anterior lateral microtubule (ALM). Depending on the orientation of the immobilized worm, the axotomy was performed on either left or right ALM neuron (ALML or ALMR). We used the strain SK4005: zdIs5 (Pmec-4::gfp) + lin-15(+) I, which expresses GFP in the six touch receptor neurons [157]. Populations of age-synchronized worms were prepared by collecting and
50 isolating embryos following hypochlorite treatment. Developmental synchronization resulted in a low degree of variability in worm’s body length, which significantly improved identification rates of target neurons. Gravid adults were lysed with a small volume of a 2:1 mixture of sodium hypochlorite and 4 M sodium hydroxide, and the collected eggs were suspended in the M9 buffer overnight on a rocker to aerate. The embryos hatched overnight and were arrested in the L1 stage until the food was reintroduced. The L1 larvae were then placed on agar plates and allowed to grow for 48 hours, at which point the larvae had grown into worms at the young to mid-L4 stage and could be collected for use.
3.7.4 Laser axotomies and post-surgical imaging on agar pads
To compare the overall effects of on-chip axotomies with a traditional approach, we also performed manual axotomies on worms immobilized on agar pads with anesthetics. Agar pads were prepared by sandwiching 0.3 mL of melted 4% agar between two microscope slides that were then pulled apart upon cooling to create a flat and uniform surface. For anesthetization, we transferred worms with a capillary tube filled with 10 µL of 10 mM levamisole solution onto the center of the agar pad. A coverslip (18×18 mm, no. 1.5) was placed on top of the worms just prior to laser axotomy. All manual axotomies were performed on the same opto-mechanical setup used for automated surgeries. Subsequent imaging of recovering worms was performed on agar pads using an Olympus microscope (BX-51) with a 60×, NA=1.42, oil immersion objective. A statistical analysis of the reconnection data was conducted using the Fisher’s Exact Test.
3.7.5 Microfluidic chip priming and preparation for axotomies
The microfluidic chip was primed for each experiment by first introducing M9 solution into the flow layer inlets and letting it pass through the chip and exit from the outlets for ~5 min. This priming procedure helped to eliminate any residual bubbles within 51 the tubing. All of the flow layer inlets were pressurized to ~135 kPa. After priming the flow layer with the M9 solution, we closed all outlets with metal plugs and pressurized all control valves to ~205 kPa with DI water for 15 min. This procedure replaced the air within the valves with DI water by forcing the air to diffuse out into the PDMS. Before performing each set of axotomies, the axial (z) offset between the focal plane of the camera and the beam waist location of the laser was experimentally determined. To determine this offset, the closest surface of the glass slide was brought into camera focus and a small laser ablation spot was created on the surface by delivering a train of 300 pulses at 10 nJ/pulse. This ablation spot on the surface of the slide appears as a small dark circle surrounded by a lighter circle. The objective was then moved in 0.25 µm steps towards the ablation spot until the smallest two-dimensional (2D) ablation profile was observed. The resulting location refers to the smallest laser beam waist location; which was typically about 0.5 µm for our microscope setup. Moving deeper towards the glass slide, the Gouy Phase Shift of the laser beam was observed. The phase shift location refers to the axial position where the 2D ablation profile transitions from a bright to a dark color; which was typically about 0.9 µm for this setup. To achieve repeatable and physically consistent ablations on axons, ablations were performed by defocusing 0.5-0.9 µm below the focal plane of the visible light.
3.8 CONCLUSIONS
Here in this work, a fully automated microfluidic platform for performing laser axotomies in living C. elegans was successfully built, demonstrated, and validated. The autonomous system successfully cut axons in average 67% of the worms loaded into the microfluidic device, and the process of automated targeting and axotomy required 17 seconds for each worm. There were no statistically significant differences found for
52 reconnection probabilities between axotomies performed manually using anesthetics and our automated approach for two different ablation conditions. For future work, this axotomy chip could be connected downstream of the multiwell population delivery device we recently developed to significantly improve its throughput capacity [121]. With the combined population delivery – axotomy system and the high- speed, automated confocal imaging platform, it might eventually be possible to perform a genome-wide screening for individual genetic mediators of axon regeneration within a reasonable period. Finally, the presented image processing methodology can be adapted for ablation of PLM and AVM neurons with the incorporation of small changes to the algorithm in Step 3 of the automation process. Additionally, the microfluidic platform can be used as a phenotype screening platform with modifications to the image processing algorithm.
53 Chapter 4: A Microfluidic “Worm Hospital” for Axotomy, Recovery, and Imaging of Caenorhabditis Elegans
This chapter discusses a microfluidic multitrap parallel chip, “worm hospital”. The parallel microfluidic chip allows on-chip axotomy, post-surgery housing for recovery, and imaging of nerve regeneration all on a single chip. Utilizing the “worm hospital,” the role of neurodevelopmental genes in the Wnt/Frizzled pathway on the regenerative capacity of two touch receptor neurons was investigated. It was observed that those neurodevelopmental genes in the Wnt/Frizzled pathway are important for regeneration of two touch receptor neurons (ALM and PLM). The results from the knockout mutant studies were also compared to RNAi knockdown of the same genes using a neuronal RNAi- hypersensitive strain. In the RNAi group, we observed similar reconnection phenotypes for ALM neurons but not for PLM neurons due to possible inefficient dsRNA uptake of tissues near the tail.
4.1. INTRODUCTION
Traditional worm handling techniques of axotomy and post-surgery imaging of nerve regeneration are time consuming and labor-intensive. Recent developments in the microfluidic technology have allowed researchers to investigate nerve regeneration after femtosecond laser axotomy with a greater precision and higher throughput than conventional axotomy approaches [12, 14, 16, 127, 128]. These platforms offer many unprecedented capabilities in trapping, immobilizing, and precise laser axotomy. However, they are multi-layered PDMS devices, which are too complicated to manufacture, and operate for non-expert users. In contrast, simpler devices with a single PDMS layer are easier to use, but are limited in their lower throughput and reduced capability of orienting the worm body for precise optical manipulation.
54 Researchers attempting to perform axotomies in C. elegans have to immobilize worms in an efficient way allowing the animals to be examined for any hours post-surgery. However, conventional methods hinder the throughput and repeatability of laser axotomy experiments in C. elegans. To minimize the mistakes in the procedure and ensure the reproducibility of the experiments, microfluidic devices have been designed to manipulate the worms safely. In the last decade, microfluidic platforms have improved the throughput and the repeatability of the experiments in various C. elegans studies [13, 97, 158]. Various microfluidic assays have been developed for lifespan analysis [113, 136], neuro- developmental studies [116, 159] , phenotyping [118, 119], behavioral studies [31, 38, 102], electrophysiology [160], and laser surgery [12, 119, 127, 129]. For immobilization of the nematode for on-chip subcellular resolution laser surgery and interrogation, different microfluidic platforms have been developed by our group and others [12, 16, 127-129,
135]. In one recent on-chip surgery study, Chung et al. developed a microfluidic platform to ablate cell bodies at a rate of 110 worms per hour [129]; however, this microfluidic platform constituted three separate layers, including a cold-fluid layer, restriction valve layer, and flow layer, making the fabrication and operation of the chip complex. In order to achieve a high degree of immobilization for laser axotomy, the most common methodology has been pressurized membranes to exert adequate force for complete immobilization [12, 16, 127, 128]. The microfluidic chips employing membrane-based immobilization are double layer microfluidic chips that utilize multilayer soft lithography [94, 95]. Despite the improved immobilization capability and processing rate, multi-layer surgery platforms are very difficult to fabricate and operate, and have high device-to-device performance variation. Moreover, all these microfluidic chips require the transportation of 55 processed worms out of the chip after the surgery for recovery [12, 16, 127, 129]. In another attempt of on-chip laser surgery, a single-layer multi-trap microfluidic device has been developed to ablate single synapses [135]. This microfluidic chip uses tapered channel geometry as in [136] for immobilizing the worms in trapping channels. However, post- surgery housing and imaging were limited to a couple hours due to the lack of a separate housing and feeding area. More importantly, the tapered geometry led the worms to rotate the anterior-posterior axis plane of their bodies away from the glass interface as the channel width becomes smaller than its height [69]. This body orientation requires the laser beam to go through the cover glass and a significant portion of the worm body, leading to unsuccessful axotomies and low-contrast imaging of the lateral neurons [69]. To overcome these limitations, I have developed a parallelized microfluidic chip “worm hospital” that allows on-chip axotomy, post-surgery housing, and imaging all on a single device. The microfluidic platform features 20 trapping channels for laser axotomy and subsequent post-surgical imaging, and a perfusion area for housing the worms after laser axotomy. The microfluidic platform is designed to rapidly orient and immobilize larval stage 4 (L4) worms for on-chip femtosecond laser axotomy and young adult stage worms for optical interrogation of neuronal regeneration after 24 h of on-chip housing.in intact C. elegans, respectively. This microfluidic platform is a single-flow layer device, reducing the fabrication and operation complexity of the chip, especially for non-expert users. Utilizing the new parallel microfluidic platform, several neurodevelopmental genes associated with axonal guidance in the Wnt/Frizzled family of ligands and receptors [161- 169] were screened for changes in axonal reconnection rates of ALM and PLM neurons via loss-of-function mutant strains and RNAi gene knockdown methods.
56 4.2. DEVICE DESIGN AND OPERATION
4.2.1. Microfluidic device design
The new parallel microfluidic axotomy chip includes two main compartments. The main goal was to enable complete nerve regeneration studies inside a single device without the need for transferring them between the axotomy, recovery, and follow-up imaging procedures. The chip includes a set of 20 parallel immobilization channels for axotomy and imaging of the nematodes and a perfusion area for their housing and feeding after the axotomy and during post-surgery recovery (Figure 4.1a). There were three design considerations for the geometry of immobilization channels: (1) immobilize the worms with a desired lateral orientation to ensure the axon of interest is in the proximity of the glass interface during axotomy and imaging for optimal optical access to the axons, (2) achieve a high degree of immobilization of L4 as well as young adult stage worms, and (3) trap and immobilize only one single worm in each channel. With these requirements in mind, a tapered geometry design was demonstrated as demonstrated in [56] to trap and immobilize the worms with a pressure-driven flow. While the early design of tapered channel geometry ensured the high-degree immobilization [136], the lateral orientation of the worms was arbitrary [69], which can be unfavorable for axotomy and post-surgical imaging. In tapered immobilization devices utilizing a monotonically decreasing aspect ratio [113, 135, 136], the worms rotate their lateral axis plane away from the cover glass interface [69]. To get the best optical access to the lateral neurons (ALM or PLM) and avoid rotation of the worms during immobilization, a novel varying aspect ratio design [56] for the immobilization channels (Figure 4.1b) was incorporated. This parallel microfluidic axotomy chip consists of an array of 20 tapered parallel trap channels with variable cross-sectional aspect ratios along the channel length
57 to immobilize and orient L4 and young adult stage C. elegans for axotomies and post- surgical sub-cellular fluorescent imaging (Figure 4.1b-d). A fourth layer (shown in yellow, Figure 4.1a) consisting of sieved side perfusion channels attached to the perfusion inlet and outlet was incorporated to successfully house the worms for subsequent imaging and regeneration studies over a 24 hour period. The 20 sieved perfusion structures on each arm (8 m × 10 m) were small enough to prevent worms from passing through them but large enough to allow the liquid culture medium to perfuse food through the housing chamber. The perfusion arms were designed asymmetrically, resulting in different hydraulic resistance values. The low resistance arm (perfusion outlet) was essential for removing worms carefully from the immobilization channels after surgery without using a high pressure. The high resistance arm (perfusion inlet) was necessary to reduce the food perfusion flow rate to roughly 1 nl/s, which was determined empirically. The food perfusion was achieved through a positive pressure gradient between the inlet and outlet perfusion arms. To obtain the pressure gradient, a 5-mL fluid reservoir with a bacterial food suspension was connected to the perfusion inlet and placed at a vertical position such that the reservoir fluid line was 4 cm above the opening of the tubing connected to the perfusion outlet. The slow perfusion rate allowed worms to swim freely and feed without excess stress or having their bodies pushed up against the sieve structures during the post- surgical incubation period. The circular pillars in the housing area and the side perfusion arms provided structural stability to prevent collapse of the large PDMS chambers during fabrication and operation of the device. To accommodate all different heights, a four-layer SU-8 device mold was fabricated to make a simple-to-operate one-layer PDMS chip (Figure 4.1c). Worm entrance and exit channels were fabricated to a thickness of 60 m (shown in blue; Figure 4.1a) to 58 reduce physical stress on worms inside the chip during the loading process and post-surgery incubation, and to avoid any undesired clogging in the exit area. The narrowest channel section (Z2 in red, Figure 4.1a) has the longest channel length of 1.8 mm (Figure 4.1b). A relatively long channel ensures the trapping and immobilization of worms at different developmental stages ranging from young L4 (for initial trapping and axotomy) to young adult (for retrapping and imaging subsequent nerve regeneration).
59
Figure 4.1: Worm Hospital overview. a) A schematic top-view of the worm hospital. The immobilization channels are used to immobilize the nematodes for laser axotomy and post-process imaging. Synchronized worms are loaded into the microfluidic chip through the worm inlet. On-chip feeding post-surgery is achieved through a pressure gradient between the perfusion inlet and outlet. Heights of each distinct part of the chip are shown in different colors: sieve structures and perfusion arms are in orange (9 µm), the smallest height in the immobilization channel is in red (20 µm), the second highest channel height is in green (35 µm), and the exit outlet, perfusion area, and largest height are in blue (60 µm). b) The aspect ratio of width (w) to channel height (h) along the immobilization channel are represented as a function of channel length. The channel length starts from the interface between the perfusion area and each individual trapping channel to the exit outlet. c) Micrograph of the dye-filled microfluidic device (scale bar = 1 mm). d) 20 immobilization channels filled with L4 stage worms with an applied pressure of ~65 kPa (scale bar = 250 µm). Each immobilization channel in (d) was filled with a single worm.
60 4.2.2. Microfuidic flow process
The sequence of valve actuation and flow progressions for each step is shown in Figure 4.2. A population of ~50-70 worms suspended in M9 solution is loaded through the main inlet into the individual immobilization chambers by blocking the flow at the perfusion connections (Figure 4.2a). This loading process takes about 3 mins. After filling most channels with a single worm, extra worms in the perfusion area are pushed out of the chip by opening the worm inlet and pressurizing the perfusion inlet and outlet to a pressure of ~100 kPa (Figure 4.2b). To push the trapped worms further inside the channels and immobilize them, the main inlet is pressurized with a head pressure of ~55 kPa and a pressure gradient is achieved between the main inlet and waste outlet by closing the perfusion connections (Figure 4.2c). After immobilization, laser axotomy is performed on each immobilized worm (Figure 4.2c). Upon completion of axotomies on all trapped worms, worms are then pushed into the perfusion area by pressurizing the waste outlet and letting the flow go through the 10µm height sieve structures, after which the axotomized worms are housed and fed on-chip (Figure 4.2d). The axotomized worms are fed via a pressure gradient between perfusion inlet and outlet while the main inlet and the waste outlet connections are blocked (Figure 4.2e). To supply a constant supply of food (bacteria) in S-medium similar to [113], the perfusion inlet is connected to a 5-ml syringe that was filled with bacteria in S-medium and the perfusion outlet is connected to atmospheric pressure. After 24 h of on-chip housing and feeding, the worms are again pushed back into
61 the single immobilization chambers by pressurizing the main inlet for high-resolution post- surgery recovery imaging of nerve regeneration (Figure 4.2f).
Figure 4.2: The flow progress on the serial microfluidic chip a) A schematic of the Worm Hospital showing the microfluidic connections. This initial step is the initial loading of worms in the immobilization chambers. Worms are pushed into the device using a syringe while the perfusion connections are blocked, which helps to have a uni-directional flow between the worm inlet and the exit outlet. b) After most of the immobilization chambers are filled, the remaining worms are pushed out of the microfluidic chip by opening the worm inlet and applying pressure from the perfusion connections. c) Following cleaning of the perfusion area, laser axotomy is performed on each immobilized worm. Trapping and immobilization are sustained with the pressure gradient between the worm inlet and the exit outlet throughout the process. d) The axotomized worms are pushed back into the perfusion area for on-chip feeding and housing by creating a pressure gradient between the exit outlet and the perfusion connections. e) After all the axotomized worms are pushed back to the perfusion area, worms are fed through a slow perfusion between the perfusion inlet and outlet for 24h. f) For imaging the nerve regeneration and axonal reconnection, the axotomized worms are pushed back into the immobilization channels.
4.3. RESULTS
4.3.1. Trapping and orientation characterization
The overall success of our on-chip process depends on the efficiency of initial trapping of worms prior to axotomy and on the efficiency of retrapping housed worms for
62 imaging 24 h later. For achieving high efficiencies for both trapping and retrapping, several design iterations were carried out. These design iterations led to a single layer microfluidic device (Figure 4.1). The general design considerations included the following features: (1) Using the same trapping channels for both L4 (30 m in diameter, 600 m in length) and YA stage worms (40 m in diameter, 800 m in length) having substantially different diameters and lengths. (2) Having one single worm in each immobilization channel during both initial trapping and retrapping after 24 h on-chip recovery. In the initial designs, slightly longer immobilization channels were used. In the first couple of iterations, the length of shortest channel height (red in Figure 4.1a) was 2.0 mm whereas it is 1.8 mm in the current design. Slightly longer channels (2.0 mm) led to observation of a high frequency of immobilization channels filled with multiple worms. This problem was solved by decreasing the length of the shortest layer in the immobilization channel.
One of the initial design efforts was to optimize sieve structure geometry, which was used to feed axotomized worms during 24 h recovery period. The sieve structures were at the same height as the shortest channel height (~20 µm) of immobilization channels in our initial designs, which led to having worms stuck between sieve structures during perfusion and pushing worms back to housing chamber. In the final design, the fourth layer at ~10 µm height (shown in yellow, Figure 4.1a) was incorporated. This additional layer enabled an optimum flow rate for feeding and keeping the axotomized worms inside the perfusion area without having them stuck between sieve structures. In general, a very high trapping efficiency of the L4 stage worms during initial immobilization was observed that was necessary to perform the highest precision axotomy (Figure 4.3a). The trapping efficiency slightly reduced for YA worms after 24 h recovery due to the substantial change in worm size (Figure 4.3b). 63 The initial trapping efficiency was characterized for two different on-chip immobilization conditions (no levamisole and 0.625 mM levamisole) over 158 experiments. On average, it was found that the initial loading efficiency is higher than 90% for both immobilization conditions. The initial trapping efficiency was 94.6 ± 1.1% (N=67 experiments) for on chip immobilization with no-levamisole condition and 91.9 ± 1.0% (N=91 experiments) for on-chip immobilization with 0.625 mM levamisole condition (Figure 4.3c). The main failure mechanisms for initial trapping were (i) clogging of the immobilization channels during worm loading and (ii) trapping of more than one worm in a single channel. Clogging was caused by the introduction of agar particulates during initial trapping, whereas multi-animal trapping in a single channel was due to undesired and asynchronous development within the C. elegans population. After 24 h of on-chip incubation, the nematodes were pushed into trapping channels for scoring the axonal regeneration and reconnection via imaging. The number of worms that could be recovered and re-trapped after 24 h of housing were compared to the number of the worms initially trapped on the same chip. Specifically, I wanted to ensure that all the axotomized worms can be retrapped after 24 h of housing by having one axotomized worm in each channel and not losing any axotomized worms in the fluidic connections during recovery. The retrapping efficiencies were similar for the two on-chip conditions. The efficiencies for the retrapping step were found to be 83.3 ± 2.0% (N=67 experiments) and 85.3 ± 1.5% (N=91 experiments) for the no-levamisole and 0.625 mM levamisole conditions respectively (Figure 4.3d). There was no significant difference between two initial trapping efficiencies of the two groups. The head/tail orientation of the immobilized worms during initial trapping and 24 h after retrapping for two different immobilization conditions was also characterized (Figure 4.4). For all immobilization conditions, it was
64 found that approximately 50% of the worms were immobilized with their heads oriented towards the exit outlet during both initial trapping and 24 h after retrapping.
65 Figure 4.3: Trapping and retrapping efficiency characterization. Trapping and retrapping efficiencies. a) Top-views of parallel immobilization channels with immobilized young L4 stage animals (left) and young adult (YA) stage worms after 24 h on-chip housing (right). Out of 20 single immobilization channels, 19 contained a single immobilized worm (marked with green circles) and only one of the channels was empty (marked with red circles). Out of 19 initially processed animals, 17 were successfully re-trapped. (scale bar = 200µm) b) The zoomed-in images show two adjacent channels each containing a single immobilized animal with different head-and-tail orientations during initial trapping (left) and retrapping (right). (scale bar = 100µm) c) The initial trapping efficiencies with and without anesthetics show no statistically significant (ns) difference between the trapping efficiencies. Error bars show the standard error of mean and the number (N) in each bar indicates the number of performed experiments. A two-tailed test was used for statistics (ns – not significant).
66
Figure 4.4: Head-tail orientation characterization. a) The percentage of the head-tail orientation of worms during initial trapping for the two different on- chip immobilization conditions. For initial trapping for no-levamisole on-chip conditions, 53.9 ± 1.5% of the axotomized worms are immobilized as their heads are in the direction of the exit outlet whereas 52.1 ± 1.5% had the same orientation for 0.625mM levamisole on-chip immobilization conditions. (two tailed t- test p>0.05). b) The percentage of the head/tail orientation of worms 24h after post-surgery recovery for the two different on-chip immobilization conditions. For post-surgical trapping for no-levamisole on-chip conditions, 55.9 ± 1.8% of the axotomized worms are immobilized with their heads towards the exit outlet whereas 51.5± 1.5% had the same orientation for the 0.625mM levamisole on-chip immobilization condition. (two-tailed t-test; ns , not significant). Error bars in a and b show standard error of the mean and the number (N) in each bar indicates number of experiments.
4.3.2. Viability test
A viability test was carried out to assess the effect of on-chip immobilization and 24h on-chip housing on worm survivability. There were two different trial groups. One group was immobilized on-chip without levamisole and the other group was immobilized with the aid of 0.625 mM levamisole. Control and two trial groups underwent the same synchronization and cleaning procedures. The control group was not subjected to any on- chip manipulation. Both trial groups were subjected to an initial immobilization for 20 mins with a head pressure of 55 kPa, on-chip housing for 24h and re-immobilization for 20 mins again with a head pressure of 55 kPa. After re-immobilization, both trial groups were
67 flushed out of the chip and collected on NGMSR plates. The viability of the worms in each population was evaluated every 24 h and worms were transferred to new NGMSR plates whenever necessary. The average lifespan of the immobilized groups were found to be 19.8 ± 3.7 and 19.1 ± 5.0 days for on-chip immobilization with no levamisole and 0.625 mM levamisole, respectively. The average lifespan for the control group was 19.2 ± 3.8 days. The Log-Rank test was used to determine the difference between the viability of each group. No statistically significant difference (p>0.90) in outcome was identified among the three groups (Figure 4.5).
Figure 4.5: Lifespan analysis. The viability of worms immobilized on-chip for two different conditions (without levamisole in blue and 0.625mM levamisole in orange) were compared to the viability of a control group. (Log-Rank test, p>0.90, not significant).
68 4.3.3. Axonal regeneration results
Using the parallel axotomy microfluidic chip, the regenerative effects of several genes in the Wnt/Frizzled family of ligands and receptors were studied, which are known to be involved in axonal guidance and axonal polarity. For the mutant animals, transgenic line zdIs5: (mec-4::GFP), expressing GFP in six touch receptor neurons was used. Subsequently, the same genes were also tested using the RNAi-hypersensitive strain TU3595: uIs72 [pCFJ90 (Pmyo-2::mCherry), Punc-119::sid-1, Pmec-18::mec-18::gfp]; sid-1(pk3321) him-5(e1490); lin-15b(n744)) to understand whether similar results can be observed to single mutants targeting the same genes. Before screening the genes in the Wnt/Frizzled pathway, it was important to understand whether on-chip axotomy had an effect on the reconnection rates. On-agar axotomies were carried out as a control for both mutant and RNAi assays and compared to on-chip axotomy reconnection results. To determine axonal reconnection rates following on-chip laser axotomies, we used two primary criteria to describe a robust reconnection: (1) proximal re-growth trajectories intersecting the distal axon and (2) a lack of beading or fragmentation in the distal axon that normally marks the beginning of Wallerian degeneration [18, 143]. Figure 4.6a shows fluorescence images of regrowth of a severed axon lacking reconnection from a worm axotomized and imaged on-chip. The regrowth with a lack of reconnection is evident by a dimmed GFP signal and by beading in the distal part of the axon (Figure 4.6a). Figure 4.6b shows an example of axonal reconnection of an ALM neuron 24 hr after the on-chip surgery. On-agar axotomies for both ALM and PLM neurons of mutant (Figure 4.6c) and RNAi (Figure 4.6d) control animals (Table 4.1 and 4.2) were performed. For the mutant control assay, control animals with zdIs5 transgene background (SK4005) were used, whereas neuronal RNAi-hypersensitive (TU3595) animals were fed 69 with empty RNAi vector L4440 were used as a control for the RNAi assay. There were no statistically significant differences for reconnection probabilities between axotomies performed on-agar using anesthetics and those carried out on-chip for both ALM and PLM neurons of both mutant and RNAi control animals (Figure 4.6c and d).
Figure 4.6: On-chip imaging of axonal regrowth and reconnection 24 h after surgery, and comparison of on-chip axotomy performance to on-agar axotomy using anesthetics. a) False-colored images of axonal regrowth of PLM neuron of a cfz-2(ok1201) mutant animal showing a lack of reconnection that is evidenced by the severed ends taking paths in different focal planes and fragmented beading in the distal end. Each image refers to different z locations. b) Images at three different z-locations showing an example of reconnection of an ALM neuron of cwn-1(ok546) mutant animal. The arrow indicates the connection point of distal and proximal ends. c) Axonal reconnection rates of the ALM and PLM neurons of control animals with zdIs5 transgene background for two different surgical conditions, which are on-chip immobilization and on-agar using anesthetics. There were no statistically significant differences observed between the percentage of axonal reconnection of the two axotomy conditions for ALM neurons (Two-tailed t-test p=0.79) and PLM neurons (Two-tailed t-test; ns, not significant). c) Comparison of axonal reconnection rates of the two different axotomy conditions for both ALM and PLM neurons of the RNAi control assay. For this RNAi control assay, RNAi-hypersensitive (TU3595) animals are fed with empty RNAi vector L4440. There were no statistically significant differences observed between the axonal reconnection rates of two axotomy conditions for ALM neurons (Two-tailed t-test; ns, not significant) and PLM neurons (Two-tailed t-test; ns , not significant). The scale bars in a) and b) are ~15 µm. The error bars in c) and d) show standard error of proportion and the number (n) in each bar indicates the number of animals.
70 Genotype or Reconnection Number of dsRNA Condition rate% p-value animals (n) feeding and (n)
zdIs5 On-chip 81 81.5% (66) p=0.75 zdIs5 On-agar 32 84.4% (27)
L4440 On-chip 28 85.7% (24) (control RNAi) p=0.11 L4440 On-agar 21 66.7% (14) (control RNAi) Table 4.1: Comparison of on-chip and on-agar axonal reconnection percentages of ALM neurons in single mutant and RNAi experiments.
Genotype or Reconnection Number of dsRNA Condition rate% p-value animals (n) feeding and (n)
zdIs5 On-chip 97 54.6% (53) p=0.46 zdIs5 On-agar 38 47.4% (18)
L4440 On-chip 39 64.1% (25) (control RNAi) p=0.65 L4440 On-agar 19 57.9% (11) (control RNAi) Table 4.2: Comparison of on-chip and on-agar axonal reconnection percentages of PLM neurons in single mutant and RNAi experiments.
4.3.4. Axonal growth and guidance, and neuronal polarity genes
The connectivity and formation of the nervous system are guided by phylogenetically conserved small molecules [161, 162, 170]. Several developmental processes are affected by mutations in these genes including cell migration, neuronal polarity, axonal guidance and branching, and axonal branching [161-166, 170-173]. There are five Wnt ligands (LIN-44, EGL-20, CWN-1, CWN-2, and MOM-2) present in C. 71 elegans genome, one or more mutant alleles are present for each ligand. Additionally, there are four Frizzled receptors corresponding to these five Wnt ligands: MIG-1, CFZ-2, MOM- 5, and LIN-17 [173]. To the best of our knowledge, there has not been any study on whether these developmental genes have an effect on axonal regeneration process of ALM neurons. Only a few genes from Wnt/Frizzled were screened for their effect on the regeneration capability of PLM neurons [3]. Using the parallel microfluidic chip, certain axonal guidance molecules of Wnt/Frizzled family were studied to understand whether these genes are involved in the axonal regeneration processes of ALM and PLM neurons. Instead of only looking at neuronal regrowth, it was worthwhile to check whether the genes are inhibiting or enhancing reconnection. In this dissertation, the effects of these genes on regeneration within the scope of reconnection rather than regrowth alone were studied. Single mutant strains of the following genes in the zdIs5 background and, subsequently, RNAi knockdown: cwn-1, cwn-2, egl-20, mig-1, cfz-2, and dlk-1 were studied for this dissertation research. I used dlk-1 mutant animals as a positive control because the DLK-1 kinase pathway is essential for axonal regrowth following injury and dlk-1 mutant animals show very little to no regeneration [3, 15, 79]. The cwn-1, cwn-2, cfz- 2, mig-1, and dlk-1 mutations significantly decreased the reconnection possibility in ALM neurons, whereas only egl-20 mutant animals did not show any significant decrease with respect to control animals (Figure 4.6a and Table 4.3). The double mutant egl-20 and cwn- 1 were shown to regulate neuronal polarity in ALM neurons where single mutant animals did not show any effect [165]. Similar to other nerve regeneration studies [3, 15, 79], dlk- 1 mutant animals showed very low reconnection in ALM neurons. The single mutants of egl-20 and cwn-1 showed the smallest decreases in the reconnection possibility (about 6.5% and 38.1%). It was observed that cwn-2 and cfz-2 mutations, which were previously shown to inhibit regrowth in PLM neurons [3], also significantly decreased the 72 reconnection rate in ALM neurons. RNAi-mediated gene knockdown for the same genes was also performed to understand whether we can echo the mutant data for ALM neurons (see Figure 4.6a and Table 4.4). Except cwn-2, similar trends to mutant animals in RNAi knockdown animals were observed.
Reconnection Number of Genotype rate% p-value to zdIs5 animals (n) and (n) zdIs5 81 81.5% (66)
cfz-2(ok1201); 38 28.9% (11) p<0.001*** zdIs5 cwn-1(ok546); 30 43.3% (13) p<0.001*** zdIs5 cwn-2(ok895); 40 20.0% (8) p<0.001*** zdIs5 dlk-1(ju476); 31 6.5% (2) p<0.001*** zdIs5 egl-20(n585); 24 75.0% (18) p=0.492 zdIs5 mig-1(c1787); 48 14.6% (7) p<0.001*** zdIs5 Table 4.3: On-chip axonal reconnection percentages of ALM neurons in single mutant animals.
73 Reconnection Number of dsRNA feeding rate% p-value to control animals (n) and (n) L4440 28 81.5% (24) (control RNAi)
cfz-2 21 42.9% (9) p<0.001***
cwn-1 19 57.9% (11) p=0.028**
cwn-2 22 72.7% (16) p=0.251
dlk-1 20 20% (3) p<0.001***
egl-20 21 71.4% (15) p=0.218
mig-1 20 45.0% (9) p=0.002**
Table 4.2: On-chip axonal reconnection percentages of ALM neurons with RNAi gene knockdown.
For PLM neurons, the mutations egl-20, cwn-2, mig-1, cfz-2 and dlk-1 significantly decreased the reconnection rate whereas only cwn-1 mutant animals did not show any significant decrease in the reconnection rate with respect to control animals (see Figure 4.7b and Table 4.5). Similar to the regrowth results of [3], it was observed that the mutations egl-20, cwn-2, and dlk-1 inhibit the reconnection rate and cwn-1 mutant animals did not show any significant decrease in the reconnection possibility (Figure 4.7b and Table
4.5). Similar to the reconnection results of mutant animals for ALM neurons, it was also observed significant inhibition of regrowth with mig-1 and cfz-2 animals. RNAi-mediated gene knock-down for the same genes for the PLM was also pursued. In contrast to RNAi gene knock-down results for ALM neurons, the gene knock-down does not echo the mutant data in terms of reconnection rates (Figure 4.7b and Table 4.6). One possible reason for unsuccessful RNAi knock-down in PLM neurons may be that induction by feeding is due to ineffective at affecting the tail region of the TU3595 strain [39, 174]. 74
Reconnection Number of Genotype rate% p-value to zdIs5 animals (n) and (n) zdIs5 97 54.6% (53)
cfz-2(ok1201); 34 5.9% (2) p<0.001*** zdIs5 cwn-1(ok546); 27 33.3% (9) p=0.051 zdIs5 cwn-2(ok895); 35 8.6% (3) p<0.001*** zdIs5 dlk-1(ju476); 47 2.1% (1) p<0.001*** zdIs5 egl-20(n585); 34 29.4% (10) p=0.011* zdIs5 mig-1(c1787); 28 14.3% (4) p<0.001*** zdIs5 Table 4.5: On-chip axonal reconnection percentages of PLM neurons in single mutant animals.
Reconnection Number of dsRNA feeding rate% p-value to control animals (n) and (n) L4440 39 64.1% (25) (control RNAi)
cfz-2 19 52.6% (10) p=0.395
cwn-1 20 80.0% (16) p=0.218
cwn-2 21 38.1% (8) p=0.051
dlk-1 20 20.0% (5) p=0.003**
egl-20 20 60.0% (12) p=0.760
mig-1 20 14.3% (4) p=0.031*
Table 4.6: On-chip axonal reconnection percentages of PLM neurons with RNAi gene knockdown. 75
Figure 4.7: On-chip axonal reconnection results for the selected genes in WNT/Frizzled family. Quantification of the successful reconnections with different genetic backgrounds by mutant and RNAi knockdown studies in ALM neurons (a) and PLM neurons (b). The number adjacent to each bar indicates the number of animals processed. The p values from two-tailed t-test: *0.01 76 4.4 EXPERIMENTAL METHODS 4.4.1 Device fabrication Standard soft-lithography techniques were used to fabricate the single PDMS layer axotomy chip [91]. The resultant photoresist pattern, produced using Mylar masks (CAD/Art Services), was used to create the master mold for all polydimethylsiloxane (PDMS; Sylgard 184, Dow Corning Corp) structures. There were four photolithography steps to create the master mold. To begin, a 4"wafer was spin-coated with SU-8 2007 photoresist (Microchem Corp.) at 1600 rpm for 33 s to obtain a uniform height of ~10 µm. This layer was exposed to UV light through the first patterned photo-mask to achieve Zone 1 features (Z1, orange, Figure 4.1a) using a mask aligner (MA6/BA6, Suss MicroTec). This layer was then hard baked and developed to remove the unexposed SU8 photoresist. A second layer spun at 4100 rpm atop the Zone 4 feature using SU8-2025 photoresist to obtain a height of ~20 µm. The second layer was exposed to UV light through a photo- mask with the pattern for Zone 2 (Z2, red, Figure 4.1a), as displayed in Figure 1a. After the hard bake and development of the second layer, a third layer was spin coated on top of the first two layers using SU8-2025 at 2850 rpm to obtain a uniform height of ~35 µm. This layer was exposed through a unique photo-mask, hard baked, and developed to achieve Zone 3 (Z3, green, Figure 4.1a). The fourth layer was spin coated using SU8-2025 photoresist at 1700 rpm to obtain a uniform height of ~60 µm. Similarly, it was exposed through a unique photo-mask, hard baked, and developed to achieve Zone 4 (Z4, blue) as displayed in Figure 4.1a. The resultant four layer SU8 master mold was treated with tridecafluoro-1,1,2,2-tetrahydrooctyl-1-trichlorosilane vapor (United Chemical Technologies) in a vacuum chamber at -67 KPa and 40 °C to create a hydrophobic layer on the wafer to reduce surface adhesion during the soft-lithography process. 77 The hydrophobic SU8 master mold was then used to fabricate the PDMS microfluidic chips with soft-lithography techniques. The PDMS was mixed at a ratio of 10:1 (base to curing agent), degassed in a vacuum chamber for 20 minutes to remove bubbles, and slowly poured onto the master to a height of 5 mm. The PDMS layer was cured at 70 °C for 2 h and peeled off from the SU8 mold after cooling. Individual chips were cut out using a razor and fluid interconnect holes were obtained with a 22 gauge punch using a manual punching machine (Accu-Punch MP10-UNV, Syneo). The PDMS chip was then cleaned with tape and irreversibly bonded to a cover-glass slide via oxygen plasma treatment at 100 W for 30 s (PE-50, Plasma Etch Inc.). The bonded device was then cured at 70 °C for 6 h to enhance the glass-PDMS bonding. 4.4.2. Opto-mechanical setup The laser axotomy setup incorporates custom optics to deliver femtosecond laser pulses for surgery into a home-built epi-fluorescence microscope as described in our previous works [12, 127]. Briefly, axotomies and post-surgery imaging were performed using a 63× oil-immersion objective (Plan-Apochromat, 63×, NA=1.4, Zeiss). For high- resolution imaging of green fluorescent protein (GFP) labeled axons, a mercury arc lamp (XCite 120, EXFO) passing through a FITC filter set (Semrock) provided the excitation light. A three-axis translation stage made of individual actuators (LTA-HS, Newport) and operated by a single controller (ESP301-3, Newport) positioned the samples. We used a three-axis piezoelectric actuator (MAX 302, Thorlabs) with a minimal theoretical step size of 25 nm to perform fine translation. A CCD camera (1392 × 1040 pixels with 6.45 µm pixel size, CoolSnap ES, Photometrics) was used to capture images. All axotomies were performed using a train of 300 pulses with a pulse width of 250 fs and a pulse energy of 7.5 nJ at a center wavelength of 805 nm generated at a repetition rate of 1 kHz (Spitfire, 78 Spectra Physics). The beam energy was measured with an energy meter (PJ10, Ophir) prior to performing all axotomies and adjusted with two half wave plate/polarizing cube beam- splitter pairs. The high numerical aperture objective lens tightly focused the laser beam to a spot size of about 620 nm based on the theoretical 1/e2 diameter of focused Gaussian beams (0.925 λ/NA) [175]. 4.4.3. System operation and control A modified version of our previously demonstrated automation software was used to control the hardware [127]. After trapping and immobilizing the worms, the operator moves the field-of-view near the neuron of interest (ALM or PLM) and then performs a coarse focusing and fine focusing steps [127] to ablate the axon of interest in a semi- automated manner. For post-recovery sub-cellular imaging and scoring of nerve regeneration and axonal reconnection, 14 image stacks (0.8 µm step size) were acquired and saved automatically for each previously severed axon. Fluid flow in the worm inlet, perfusion inlet, and outlet fluidic channels were controlled by pressurized external fluid chambers controlled by three-way solenoid valves (The Lee Co., LHDA0521111H). The solenoid valves were coupled to the chip through a manifold (The Lee Co., LFMX0510418). These chambers contained M9 buffer solution (22 mM KH2PO4, 22 mM Na2HPO4, 85 mM NaCl, 1 mM MgSO4, in dH2O). To minimize debris, all M9 buffer was passed through 1.2 µm in-line filters (Acrodisc, Pall Corp.) prior to entering the microfluidic device. The fluidic connections were independently actuated with a multichannel amplifier (Automate Scientific). The digital control of the amplifier was carried out by DAQ card (USB6501, National Instruments). Before each experiment, the device was primed by first introducing M9 solution into the worm inlet and perfusion inlet and outlet. This process was carried out as follows: M9 solution was flowed through the 79 exit outlet for ~2 min, followed by plugging the exit outlet for ~10 min. This priming procedure helped to eliminate any residual air bubbles within the tubing and the microfluidic chip. 4.4.4 Laser axotomy and post-surgical imaging On-chip laser axotomies and post-surgical imaging were performed as described in [127]. For this study, the axonal regrowth and reconnection to their distal ends on two of the six touch receptor neurons (ALM and PLM neurons) were studied. Depending on the orientation of the immobilized worm, the axotomies were performed on either the left or right ALM neuron (ALML or ALMR) or PLM neuron (PLML or PLMR). Only one neuron was axotomized for each hermaphrodite worm. Axotomies were performed approximately 60 µm away from the cell body for both on-chip and on-agar axotomies. Agar pads were prepared by sandwiching 0.25 mL of melted 4% agar between two microscope slides that were then pulled apart upon cooling to create a flat and uniform surface. For each on-agar experimental set, 10 µL of 10 mM levamisole solution was used to immobilize ~15 worms. A coverslip (18×18 mm, no. 1.5) was placed on top of the worms just prior to laser axotomy. On-agar surgeries and post-surgical imaging were performed using the same opto-mechanical setup used for on-chip experiments. For each set of experiments, only one type of axon was axotomized. 4.4.5 Nematode maintenance For mutant studies, C. elegans were maintained at 16.5 °C on NGM (Nematode Growth Medium) agar plates seeded with HB101 E. coli bacterial culture using standard procedures [26]. We used the following strains for mutant studies. SK4005: zdIs5 [(mec- 4::gfp) + lin-15(+)], CX6188: egl-20(n585); zdIs5 [(mec-4::gfp) + lin-15(+)], CX6219: mig-1(c1787); zdIs5 [(mec-4::gfp) + lin-15(+)], CX6429: cwn-1(ok546); zdIs5 [(mec- 80 4::gfp) + lin-15(+)], CX6787: cfz-2(ok1201); zdIs5 [(mec-4::gfp) + lin-15(+)], CX6865: cwn-2(ok895); zdIs5 [(mec-4::gfp) + lin-15(+)], CZ11327 dlk-1(ju476); zdIs5 [(mec- 4::gfp) + lin-15(+)], which express GFP in the six touch receptor neurons. Populations of age-synchronized worms were prepared by collecting and isolating embryos following hypochlorite treatment. Gravid adults were lysed with a small volume of a 2:1 mixture of sodium hypochlorite and 4 M sodium hydroxide, and the collected eggs were suspended in M9 buffer overnight on a rotator to aerate. The embryos were hatched overnight and were arrested in the larval stage 1 (L1) until the food was reintroduced. The L1 stage worms were then placed on HB101-seeded agar plates and allowed to grow for 48-50 hours until the worms reached the early to middle L4 stage. For RNAi studies, the strain TU3595: uIs72 [pCFJ90 (Pmyo-2::mCherry), Punc- 119::sid-1, Pmec-18::mec-18::gfp]; sid-1(pk3321) him-5(e1490); lin-15b(n744)) was used [174]. To get a highly synchronous population of worms, RNAi-hypersensitive worms were kept at 19.5°C. RNAi feeding plates were seeded with bacteria containing the appropriate vector for the gene of interest. To ensure that the desired phenotype was obtained at F1 progeny of the worms, the gravid adults of F0 were grown on the bacteria expressing ds-RNA of the corresponding gene of interest. Gravid adults were lysed with the same method used for mutant strains. Sometimes, the RNAi phenotype is not observable in the F0 generation [174, 176], therefore F1 generation worms were used for axotomies. The starved L1 larvae were then placed on agar plates with bacteria expressing ds-RNA of the same gene of interest. 4.4.5. Neuronal RNAi hypersensitive strain for axotomy assays RNA interference (RNAi) is a convenient method for studying the phenotypic effect of impaired gene expression. It has been established that introducing exogenous 81 dsRNA to C. elegans will partially or completely knockdown translation of mRNA at the location of interest, thus inhibiting synthesis of the protein encoded by a specific gene [177]. One advantage of using RNAi is that it is systemic in C. elegans. In other words, the double-stranded RNA can effectively spread throughout the body of the worm to knockdown the expression of a targeted gene in almost every cell [167, 177]. For systemic RNAi, the transmembrane protein SID-1 is needed for passive uptake of dsRNA [168], but SID-1 protein expression in neurons is limited [168, 178]. RNAi occurs in neurons when dsRNA is produced in the neuron itself [179]; however the penetrance of dsRNA in neurons is limited. C. elegans neurons inherently exhibit the ability to susceptibility RNAi but are unable to respond to systemic feeding RNAi due to a lack of SID-1 allowing the uptake of dsRNA in their neurons. Several neuronal RNAi-hypersensitive strains have been developed with various neuronal RNAi level [52, 59-61, 140]. More recently, Dr. Chalfie and colleagues developed a neuronal RNAi-hypersensitive strain (TU3595) that was shown to replicate the neuronal phenotype of more genes than other neuronal hypersensitive strains [174]. The strain TU3595 expresses sid-1 in all neuronal cells (Punc-119::sid-1 transgene) while blocking expression in all other cells (sid-1 mutation), thus limiting exogenous RNAi to neurons only [174]. The touch receptor neurons (TRN), including ALMs and PLMs, are labeled with GFP (mec-18::gfp transgene). This neuronal RNAi- hypersensitive strain was used to examine the reproducibility of the results of mutant studies by gene knockdown. 4.4.6. On-chip immobilization with the aid of levamisole Laser axotomy and post-surgery imaging of C. elegans require a high-degree of immobilization. In our single layer axotomy chip, the immobilization of each worm is obtained because of the geometry of the immobilization channel. Each worm is pushed 82 inside the immobilization channel until the walls of the shortest channel section (Z2 in red, Figure 4.1a and b) prevent any sinusoidal body movement such as crawling or swimming [136]. Preventing the sinusoidal body movement provides enough immobilization for axotomy on ALM neurons, located near the middle part of the worm body. However, PLM neurons are located near the tail, which still has space to move. To eliminate the motility of the tail of trapped worms, we used a low concentration of levamisole (0.625 mM levamisole) for performing axotomy on the PLM neurons. The worm suspension in M9 buffer solution with 0.625 mM levamisole was prepared as follows. First, 1 ml of M9 solution was pipetted onto worms growing on an agar pad. Second, 0.5 ml of this M9 buffer solution suspended with worms was drawn into a syringe tube containing 0.5 ml of 1.25 mM levamisole. As a result, 1 ml of 0.625 mM levamisole solution ~50-75 worms was obtained. In addition, 0.625 mM levamisole in an external fluid reservoir was used to provide buffer flow through the worm inlet during on-chip PLM axotomy and imaging. 4.5 CONCLUSIONS In this chapter, a parallel microfluidic platform the “worm hospital” for femtosecond laser axotomy in C. elegans was presented. The parallel microfluidic platform allows on-chip axotomy, post-axotomy housing, and post-surgical recovery imaging of nerve regeneration after 24 h. With this microfluidic platform, highly efficient trapping and immobilization of the worms for axotomy and post-surgical imaging were achieved; which was more than 91% for two different on-chip immobilization conditions (no levamisole and 0.625 mM levamisole). After 24 h of on-chip housing, more than 83% percent of the worms for the two different on-chip immobilization conditions were successfully recovered and retrapped. There were no any significant biases for the orientation of the immobilized worms for different on-chip conditions. Approximately half of the trapped 83 worms were immobilized with their heads orientated towards the exit outlet for all immobilizations during both initial and 24 h after trapping. Using the “worm hospital” microfluidic platform, several genes in the Wnt/Frizzled pathway for the axonal reconnection were screened on two different neurons (ALM and PLM) by first using loss-of-function mutant animals and then RNAi-mediated gene knockdown animals. It was observed that Wnt/Frizzled family were involved in the developmental process are also essential for the axonal regeneration and successful axonal reconnection after injury for both ALM and PLM neurons. Specifically, the mutations cwn- 2, cfz-2, mig-1, and dlk-1 significantly decreased the reconnection possibility for both ALM and PLM neurons. In addition, it was observed that the cwn-1 mutation significantly inhibited the reconnection in only ALM neurons, whereas egl-20 mutation significantly decreased the possibility of reconnection only in PLM neurons. Subsequently, we repeated the axotomies targeting the same genes with RNAi knockdown using a neuronal hypersensitive strain. With RNAi knockdown, a similar trend in reconnection for ALM neurons but not for PLM neurons was observed. RNAi might not be efficient within the tail region of the neuronal RNAi-hypersensitive strain TU3595 as observed before [50, 65]. This new microfluidic platform offers an easy-to-use microfluidic chip especially for non-expert end users. The capability of the microfluidic chip integrating the axotomy, housing, and post-surgical recovery imaging is promising for future high-throughput studies. 84 Chapter 5: Conclusions and Future Work 5.1 SUMMARY OF THE DISSERTATION This dissertation described the design and fabrication of two comprehensive microfluidic platforms to perform femtosecond laser axotomy in C. elegans to understand the molecular basis of nerve regeneration and degeneration at high-throughput in a controllable environment. The first microfluidic platform was a fully automated serial microfluidic platform, presented in Chapter 3. The serial microfluidic platform, to the best of our knowledge, was the first example of a microfluidic platform to enable full-automation of femtosecond laser axotomy in C. elegans. The full automation of on-chip femtosecond laser axotomy was achieved through a unique microfluidic chip design that allows the synchronization of valve actuation progress and a custom-developed software interface that incorporates image processing algorithms to sever the axon of interest in C. elegans with no human intervention. The serial microfluidic chip was designed to have distinct compartments, namely, the loading chamber to house a worm population, a staging channel to isolate a worm from the population, a trapping chamber to immobilize and perform automated laser axotomy, collection channels to transfer processed worms out of the chip, and 3D valve- like structures. For the automation software interface, an algorithm constituting four steps was developed. The serial automated microfluidic platform enabled axotomy of single neurons in C. elegans with a success rate of 67.4% (350 animals), and the process of automated targeting and axotomy required ~17 seconds for each worm. The reconnection probabilities obtained with automated on-chip surgeries did not show any significant differences compared to on-agar surgeries using anesthetics. The second microfluidic platform was a parallel multitrap axotomy chip, named “Worm Hospital” which was presented in Chapter 4. The microfluidic platform allowed 85 on-chip axotomy, and post-surgical recovery housing and imaging of nerve regeneration all on a single chip. Overall on-chip processing of animals was highly efficient. More than 91% of immobilization channels were filled with a single worm during initial immobilization. After 24 h of on-chip housing, more than 83% percent of the worms were successfully recovered and retrapped. Using the parallel microfluidic platform, the effect of neurodevelopmental genes in the phylogenetically conserved Wnt/Frizzled pathway on the reconnection possibilities of two touch receptor neurons (ALM and PLM) was investigated by both mutant animals and RNAi-mediated gene knockdown animals. 5.2 FUTURE WORK Regarding the serial automated axotomy platform, the microfluidic platform will be coupled downstream to microfluidic sorting platforms, which can potentially enable a large-scale screening of genes involved in nerve regeneration and axonal reconnection. Additionally, another microfluidic device can be coupled downstream to the serial microfluidic chip to house axotomized animals during post-surgical recovery to image nerve regeneration over a time course. These further improvements can potentiate the use of the serial automated axotomy platform for genome-wide screening of genes for nerve regeneration studies. As a future work, fabrication of the serial microfluidic device can be further optimized to minimize device-to-device variation, which is very common with double-layer microfluidic device fabrication. Another potential improvement will be to use only one microscope objective for both determining the relative location of trapped worms in the trapping area and performing laser axotomy. The parallel microfluidic device holds a great potential of being translated to other labs and used as a user-friendly axotomy technique, which can potentially replace traditional immobilization techniques. Future work with the parallel microfluidic platform 86 could include developing the current software interface so that axotomies would be performed in a fully automated manner. 87 Appendix A: Supplementary Software Document for the Serial Automated Microfluidic Femtosecond Laser Axotomy Platform for Nerve Regeneration Studies in C. elegans A.1 SOFTWARE INSTRUCTIONS AND LIST OF HARDWARE REQUIREMENTS: This appendix describes the custom-developed software used for controlling the serial microfluidic chip that was designed to perform automated laser axotomy experiments described in Chapter 3. The items included here are hardware list and screenshots of the LabVIEW front panels with a brief description of their operation. The software was written in LabVIEW 2012 platform. To properly run the software, the user must have LabVIEW 2012, LabVIEW Vision Acquisition Software, LabVIEW Vision Development Module, LabVIEW MathScript RT Module, NI Device Drivers, NI ELVISmx, µmanager (https://www.micro-manager.org/), and Matlab V2012a. This software was developed specifically for running the microfluidic system presented in the third chapter of this thesis. This custom-software was developed to run specifically with the following hardware: A.2 HARDWARE LIST Imaging and Ablation Camera: CoolSnap ES (Photometrics) Low-magnification objective: 5× air objective, Plan-Apochromat, NA=0.16 (Zeiss) High-magnification objective: 63× oil-immersion, Plan-Apochromat, NA=1.40 (Zeiss) Optical beam mechanical shutter : SH05 (Thorlabs) Optical beam mechanical shutter controller: SC10 (Thorlabs) Fluidic control Three-way solenoid valves: LHDA0521111H (Lee Company) Valve control: Valvelink 8.2 (AutoMate Scientific) Digital solenoid valve control unit: NI-DAQ Card USB 6501 (National Instruments) Position control Long-range motorized stages (3 axes): LTA-HS (Newport) 88 Motorized stage controller (3 channels): 3 axes motion controller/driver, ESP300 (Newport) Piezo translational stages (3-axes): MAX 302 (Thorlabs) Open-loop piezo controller (3-channels): MDT693A, 3-Channel, open-loop piezo controller (Thorlabs) Computer CPU: Core™ i5-2500K CPU @ 3.30 GHz (Intel) Graphics card: NVIDIA GeForce GT 520 (NVIDIA) Operating system: Windows XP Professional Version 2002 Service Pack 3 (Microsoft) Frame grabber: PCI LVDS Interface Card (Photometrics) For different camera specs, translational stages, communication settings, and/or microscope objectives’ specs, modifications to the program would be necessary.In the following sections, the details of the LabVIEW software and the associated panels are described. A.3 AXOTOMY.VI This is the main LabVIEW VI (Virtual Instrument) that controls all of the hardware listed above, performing automated axotomies, and defining all the axotomy parameters used for automation. The front panel consists of eight main tabs, as shown in Figure A.1: 1. START 2. CCD Camera 3. Motorized Stage 4. Shutter 5. Piezo Stage 6. Valves 7. ROI Locations 89 8. Automated Process Figure A.1: The front panel of Axotomy.vi with “START” tab chosen. Each tab panel is used to control different hardware components and automation parameters. The brief details of each tab is given in the following sections. 90 A.3.1. START Tab (Figure A.1): This tab is used to initiate communication with all the hardware components by simply clicking on the “START” button. After clicking the start button, the computer communicates with each associated hardware to acquire the status and communication settings of each hardware. Each sub-tab then shows the status (false/correct) of each associated hardware to inform the user if there is a communication problem between hardware and program. If the user is using a different hardware, the communication settings may have to be changed in the block diagram of the program. A.3.2. CCD Camera Tab (Figure A.2): This tab is where the operator indicates the camera exposure times for each magnification and the image file saving options for the automated process. When the program is used manually, the user can change the exposure time to a desired value by using the numerical control on the left side of the panel in the “Exposure time” section. The user may choose the file format of the saved images by changing the parameters in the middle section called “Save options for CCD Camera Images and Log File”. For the 91 automation process, the user has to define exposure times for both FOVs in the right section named “Automated Process Exposure Times”. Figure A.2: “CCD Camera” Tab. 92 A.3.3 Motorized Stage Tab (Figure A.3): This tab incorporates control parameters of the long-range translational stage that are entered manually before starting the automated process as well as for manual manipulation. To run the axotomies automatically, the operator needs to define only one parameter manually: the initial position of the stage as called “Home Position”. To define this parameter, the user needs to move the specimen to a desired location close to the immobilization area and save that location as the home position by choosing the “Home Position” item in the section called “Saved Positions Micro”. This home position serves as the initial rest position of the stage before each cycle of the automation process. The user can also store five more preset locations (in the section “Saved Position Micro”) during manual actuation for moving the stage to additional preset locations. During manual operation, the operator can move the specimen along three axes (x, y, z) by inserting the desired parameters for each axis such as acceleration, speed, and backlash compensation in the left section called “Micro Stage Data”. Manual movement of the stage can also be executed by using the graphical XY plane and Z control cursor at the bottom of the panel. 93 Figure A.3: “Motorized Stage” Tab. 94 A.3.4 Shutter Tab (Figure A.4): This tab is used to set the settings of the mechanical shutter for controlling the laser surgery beam. In the “Shutter Settings” section, the user may choose between three different shutter modes (Single, Auto, and Manual) and adjust the shutter opening/closing times. The description of each shutter toggle modes are described below. Single: In the “Single” event mode the shutter will open and close with a click on the “Send the beam” Boolean control. In this mode the shutter will remain open for the duration defined in the “Open time [ms]” and then close automatically. Auto: In the “Auto” mode the shutter will continually open and close after clicking the “Send the beam” Boolean control based on the parameters defined in “Open/Close time” windows. Manual: In manual mode the shutter will be open with a click of the “Send the beam” Boolean control and will stay open till the Boolean control is clicked again. For the automated axotomies, the operator needs to choose the “Single” mode and define opening time of the shutter in the “Open time [ms]” section. For manual axotomies, the user needs to press the “Send the beam” button to set up desired shutter modes such as 95 continuous or single-shot mode. “Send the beam” button is only used during manual manipulations. Figure A.4: “Shutter” Tab. A.3.5 Piezo Stage Tab (Figure A.5): This tab allows the user to manually control the input voltage range for the piezo driver in the sections of “Min Voltage Piezo” and “Max Voltage Piezo”. The “Coordinates Piezo Stage [um]” is used to move the piezo stage manually and “Get the position” section is used to read current position of the stage. 96 Figure A.5: “Piezo Stage” Tab. A.3.6 Valves Tab (Figures A.6-A.12): This tab accesses the state of individual valves and the timing and flow scheme of in each of the sequences in the following sub-tabs: Main Valve Control (Figure A.6) Pre-Loading Sequence (Figure A.7) Injection Sequence (Figure A.8) Immobilization Sequence (Figure A.9) Ejection Sequence (Figure A.10) Flushing Sequence (Figure A.11) Cleaning Sequence (Figure A.12) The “Main Valve Control” sub-tab is used to change the individual state of each solenoid valve control and runs the flow schemes defined in the adjacent sub-tabs. The 97 “Main Valve Control” tab also allows user to save and load the user-defined flow schemes in TDMS file format. There are six flow schemes defined in the sub-tabs (Pre-Loading Sequence, Injection Sequence, Immobilization Sequence, Ejection Sequence, Flushing Sequence and Cleaning Sequence). The first five of these sub-tabs are used in different steps of the automation sequence. The “Pre-Loading Sequence” is used to isolate one single worm from the loading area (see Figure A.7), by opening the Valve 6 for 850 ms automatically for each cycle of automation. The “Injection Sequence” is used to inject the isolated worm during the pre-loading sequence for immobilization. The “Immobilization Sequence” is used to pressurize the trapping membrane for taking background image during the automation Step 1 (see Figure A.9). The “Ejection Sequence” and “Flushing Sequence” are used to transport the processed animals to two different outlets based on whether the automation cycle was successful or not (see Figures A.10 & A.11) by opening valves V3, V2, and V4 or V5, and turning on the inlets of Pillar and Flush. The sixth and last tab includes the “Cleaning Sequence”; which is used to clean the chip by opening all the valves and turning on all the flow inlets whenever desired by clicking the corresponding Boolean controls on the “Main Valve Control” sub-tab. The order of valve steps in the schemes are saved as an array of Boolean clusters. The order of these steps is identified by the elements of the array starting with n=0 (upper left control in each scheme). For example, the first step of the injection sequence consists of turning on the side injection and opening valves V1 and V3 for 1000 ms as zeroth element (see Figure A.8a). In each of the “Sequence” sub-tabs, the user can input timings for each valve state combination to achieve the desired functionality. For individual control of each solenoid valve, there are two extra controllers defined in case the user would like to incorporate additional valve controls into the system (see 98 dashed circle in Figure A.6). These additional valves can be controlled after easily defining two digital outputs via NI DAQ MX. Control of individual valves can also be carried out using the Boolean image cluster shown as “Valves Image Cluster” at the bottom of “Main Valve Control” sub-tab (Figure A.6). The Boolean controls are placed on the picture of the axotomy chip in accordance with the actual relative locations of the valves and inlets on the chip. The closed control valves are defined by a “red X” and the open valves are left blank or defined by a “blue arrow” in the case of I/O (input or output). 99 Figure A.6: “Valves” tab and “Main Valve Control” sub-tab chosen. 100 a) b) Figure A.7: Two elements of Pre-Loading Sequence: a) Element 0: Staging a single worm from the loading chamber into the staging area by opening Valve 6 for 850 ms. b) Element 1: Default valve state. 101 Figure A.8: Four elements of the Injection Sequence: a) Element 0: Injecting the worm into the trapping area and pushing the extra worms back into loading chamber by opening Valve 1 and Valve 6 and reversing the flow in the staging side channels for 1000 ms. b) Element 1: Valve 3 is opened and c) Element 2: Valve 3 is closed in a pumping manner as described in the main manuscript before going back to default state in d) (Element 3). 102 Figure A.9: Immobilization Sequence: This sequence is the same as the default state where Valve 3 remains closed during the immobilization of the worm – so there is only one element in this sub-tab. The software waits for 500 ms in the automation sequence during image subtraction process (Step 1). 103 a) b) Figure A.10: Two Elements of Ejection Sequence: a) Element 0: Transporting the successfully axotomized worm into the recovery area through the ejection channel by turning on Flush I/O and Pillar I/O and turning off Valve 2, Valve 3, and Valve 5 for 2000 ms. b) Element 1: Returning back to default state. 104 a) b) Figure A.11: Two Elements of Flush Sequence: a) Element 0: Transporting the unsuccessfully processed worm into the waste outlet through the ejection channel by turning on Flush I/O and Pillar I/O and turning off Valve 2, Valve 3, and Valve 4 for 2000 ms. b) Element 1: Returning back to default state. 105 a) b) Figure A.12: Elements of cleaning sequence: Element 0: a) Turning on each flow inlets and de-pressurizing all control valves for 3000 ms. b) Element 1: Returning back to default state. 106 A.3.7 ROI Locations (Figure A.13): This tab is used to input information about the region-of-interests (ROI), which involves the femtosecond laser spot (the details of how to find the spot are described in the manuscript) and immobilization chamber (pre-defined ROI for Step 1 of the automation process). The ROI information should be defined before starting the automation process. Figure A.13: The front panel of Axotomy.vi with “ROI Locations” tab chosen. A.3.8 Automated Process Tab (Figure A.14): This tab allows the user to initiate the automated axotomy process by clicking the “Start” button of the Boolean control, labeled “Start the automated process”. This tab also allows the user to choose the number of worms to be processed, types of images to be saved throughout the automation process, and the offset between the focal planes of two objectives. Each of the image processing algorithms used for the automation is described explicitly in the paper. The automation algorithm flow, also described in Chapter 3, is executed automatically in the background for the desired number of worms to be processed. The success/failure of each step is saved automatically for each step. 107 Before the automation process starts, the user has to define the following parameters: File saving location. 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