90891 - Biosensors and Advanced Bioanalytical Methods

Learning outcomes

By the end of the course, students will have acquired a solid understanding of the fundamental concepts underlying the use of biomolecules as reagents in bioanalytical methods. They will be able to explain and describe the theoretical principles of detection techniques and the different experimental formats employed in bioanalytical methodologies. Students will also be able to identify, classify, and discuss the main categories of biosensors and the corresponding bioanalytical methods, as well as their applications in research and industrial settings. Furthermore, they will be able to critically evaluate different bioanalytical approaches and select the most appropriate methodological strategy to address and solve practical problems and analytical challenges.

Course contents

The course comprises a total workload of 4 CFU credits, including 3 CFU (24 hours) of lectures and 1 CFU (12 hours) of laboratory sessions.

a) Lectures (3 CFU, 24 hours)

The course begins with an introduction to biosensors, covering their definition, classification criteria, and the general principles of bioanalytical methods based on biological recognition elements and signal transduction systems. The main categories of biosensors are presented, including catalytic biosensors and affinity-based biosensors.

The module on molecular recognition elements examines the principal classes of biomolecules and artificial recognition systems employed in bioanalysis, including enzymes, antibodies, nanobodies, molecularly imprinted polymers, aptamers, nucleic acids (DNA, RNA, and PNA), whole cells, phage display technologies, and nanozymes.

The section on transduction systems introduces the principles and applications of the main signal transduction mechanisms used in biosensors, including optical, electrochemical, piezoelectric, surface plasmon resonance, and calorimetric detection.

The module on enzymatic analytical techniques covers the fundamentals of enzymology and enzyme kinetics, quantitative methods based on kinetic and end-point assays, single and coupled enzymatic reactions, detection and immobilization strategies, and their applications in enzymatic biosensors.

The section on immunological techniques addresses antibody structure and production (monoclonal, polyclonal, and synthetic antibodies), immunoassays with and without labels, homogeneous and heterogeneous assay formats, immobilization methods, competitive and non-competitive immunoassays, and cross-reactivity.

The module on Lateral Flow Immunoassays (LFIAs) focuses on design principles and structural components, the differences between competitive and non-competitive as well as direct and indirect formats, materials and labels, portable detection systems, and representative case studies.

The course also introduces gene analysis techniques, including the properties of DNA and synthetic nucleic acid analogues, electrophoresis and hybridization methods, direct and indirect labeling strategies, the principles and variants of polymerase chain reaction (PCR), including quantitative, competitive, and real-time PCR, as well as fluorescent probes and microarray technologies.

The section on DNA and RNA nanotechnology presents DNA-based nanostructures and biosensors, including DNA origami, molecular switches, and DNA tweezers, together with the principles and applications of genosensors and aptasensors.

Cell-based biosensors are then discussed, with particular emphasis on biosensors based on bacteria and human cell lines, biosensors for studying protein-protein interactions, cell immobilization techniques, and their biomedical and biotechnological applications.

Finally, students will critically analyze selected scientific publications and case studies illustrating the application of biosensors in the medical, pharmaceutical, environmental, food, and industrial sectors.

b) Laboratory sessions (1 CFU, 12 hours)

The laboratory component consists of experimental activities designed to reinforce the theoretical concepts introduced during the lectures through the practical application of the bioanalytical techniques covered in the course.

Readings/Bibliography

All teaching materials presented during the lectures, including slides and selected scientific articles, will be made available to students in electronic format through the University of Bologna's Virtual Learning Environment: https://virtuale.unibo.it/ .

For further reading:

Biosensors Nanotechnology, edited by Inamuddin and Tariq Altalhi, Wiley, 2023. DOI: 10.1002/9781394167135.

Teaching methods

The course includes classroom lectures with electronic teaching materials, made available on the Virtuale platform ( http://virtuale.unibo.it).

Single-station laboratory sessions with tutor support are also planned. Laboratory handouts will be available on the Virtuale platform.

During lectures, course topics will be presented and discussed through theoretical insights and explanatory examples. Laboratory sessions are designed to enable each student to develop practical skills, knowledge of basic analytical techniques and operational competence in a laboratory environment based on quality and safety principles.

Classroom exercises will focus on the application of statistical processing methods to experimental data obtained in the laboratory. Students will process their results and submit an individual written report on the laboratory activities.

Mandatory safety training

In view of the types of activities and teaching methods adopted, attendance requires all students, including international incoming students (e.g. ERASMUS), to complete safety training modules 1 and 2 in e-learning mode and to participate in module 3, which provides specific training on health and safety in study places. Information on dates and attendance procedures for module 3 is available in the dedicated section of the degree programme website on mandatory health and safety training.

Assessment methods

The assessment consists of an oral examinatio to evaluate the student's lknowledge on the topics covered during the lectures. The examination will assess both the student's theoretical knowledge and their ability to present scientific concepts using appropriate and rigorous terminology. Students will also be evaluated on their critical thinking skills and their ability to apply the principles learned to the solution of practical bioanalytical problems.

Students with Specific Learning Disorders (SLD) or temporary or permanent disabilities are encouraged to contact the University's dedicated support service in advance (https://site.unibo.it/studenti-con-disabilita-e-dsa/it ). The service will propose any appropriate accommodations, which must be submitted to the course instructor for approval at least 15 days before the examination. The instructor will assess the suitability of the requested accommodations in relation to the learning outcomes of the course.

Artificial Intelligence (AI) can be a valuable tool to support independent learning, for example by helping students explore topics in greater depth, summarize content or engage in self-assessment activities. Its use is therefore encouraged when it enhances learning and supports a deeper understanding of the course material.

With regard to assessment, the use of AI is not permitted during the oral examination. For laboratory reports, only a limited, declared, and non-substantial use of AI is allowed, solely for language support or the formal revision of the text. AI must not be used to process experimental data, interpret results, or generate substantial portions of the report, which must remain the student's own work.

Any undeclared or inappropriate use of AI constitutes a violation of the principles of academic integrity.

Assessment criteria

• 18-19/30: essential and partial knowledge of the topics, limited analytical ability and generally correct but not always precise use of technical language.
• 20-24/30: adequate knowledge of the main topics, ability to apply concepts to basic problems and sufficienlty correct use of terminology.
• 25-29/30: broad and well-structured knowledge, autonomous analytical ability, links between techniques and applications, and good level of technical language and terminology
• 30-30 with honours: complete and exhaustive preparation, critical autonomy, ability to connect and argue, excellent level of terminology 

Teaching tools

Teaching materials provided by the instructor and available on the Virtuale platform: http://virtuale.unibo.it.

The tools include slides, laboratory handouts, data-processing materials, possible examples of exam questions or tasks, and operational communications concerning laboratory activities.

The use of digital materials supports content accessibility and enables students to organise their study and request any necessary adjustments in good time.

Office hours

See the website of Elisa Michelini