Rapid species level identification of fish eggs by proteome fingerprinting using MALDI-TOF MS

Highlights

• Application of proteome fingerprinting for fish stock monitoring.

• 97.5% identfication success.

• Adjustment of identification scores improves identification success.

• Line of evidence from different methods improves identification confidence.

• Automatic mass spectra quality control.

Abstract

Quantifying spawning biomass of commercially relevant fish species is important to generate fishing quotas. This will mostly rely on the annual or daily production of fish eggs. However, these have to be identified precisely to species level to obtain a reliable estimate of offspring production of the different species. Because morphological identification can be very difficult, recent developments are heading towards application of molecular tools. Methods such as COI barcoding have long handling times and cause high costs for single specimen identifications. In order to test MALDI-TOF MS, a rapid and cost-effective alternative for species identification, we identified fish eggs using COI barcoding and used the same specimens to set up a MALDI-TOF MS reference library. This library, constructed from two different MALDI-TOF MS instruments, was then used to identify unknown eggs from a different sampling occasion. By using a line of evidence from hierarchical clustering and different supervised identification approaches we obtained concordant species identifications for 97.5% of the unknown fish eggs, proving MALDI-TOF MS a good tool for rapid species level identification of fish eggs. At the same time we point out the necessity of adjusting identification scores of supervised methods for identification to optimize identification success.

Significance

Fish products are commercially highly important and many societies rely on them as a major food resource. Over many decades stocks of various relevant fish species have been reduced due to unregulated overfishing. Nowadays, to avoid overfishing and threatening of important fish species, fish stocks are regularly monitored. One component of this monitoring is the monitoring of spawning stock sizes. Whereas this is highly dependent on correct species identification of fish eggs, morphological identification is difficult because of lack of morphological features.

Introduction

The correct identification of fish eggs is an important prerequisite in research of reproduction ecology of fish species [[1], [2], [3], [4]] but also for the estimation of spawning stock size of economically important fish species for assessment purposes [[5], [6], [7], [8], [9]]. However, identification of fish eggs is notoriously difficult, particularly if they are of an early developmental stage. These early stages are most often the only stages that are used to calculate egg production for spawning stock biomass estimation [1,5,8]. Apart from species of Callionymids, Beloniformes, Macrourids or Maurolicus, which have a characteristically shaped chorion, the early eggs of the vast majority of marine fish species come with no other morphological distinguishing feature than the egg diameter and presence as well as size and number of oil droplets in the yolk [10,11]. With a typical range of 0.6–2.0 mm of egg diameter and 0.1–0.4 mm for the oil droplet [10,11], there is a considerable overlap in those measures among the several marine fish species, making it almost impossible to determine the species of newly spawned eggs [12]. This is e.g. the case in the egg survey for the winter spawning fish in the North Sea [13], where cod eggs have to be separated from all other similar sized gadoid eggs or during the mackerel and horse mackerel egg survey [14], where mackerel (Scomber scombrus Linnaeus, 1758) eggs have to be distinguished from the similar sized hake (Merluccius (Linnaeus, 1758)) and ling (Molva (Linnaeus, 1758)) eggs [15]. Due to these challenges in morphological identification, a number of studies have recently focused on fish egg species identification using molecular methods such as COI barcoding [3,4,[16], [17], [18], [19]] with overall good success.

Another method for rapid and reliable species identification is Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS). This method relies on a so-called proteome fingerprint to distinguish between species [20]. Currently, this method is routinely applied in microorganism identification such as detection of bacterial pathogens [[21], [22], [23]], viruses [24,25] or fungi [26]. Aside from microbiology, nowadays MALDI-TOF MS is also applied to fight food fraud [27], e.g. to detect mislabeling of sea food species [[28], [29], [30], [31], [32], [33], [34], [35]], identify meat origin [36] or inspect milk adulteration [37]. Moreover, MALDI-TOF MS was tested in numerous studies to identify important disease vectors such as mosquitos, ticks and phlebotomine sand flies [[38], [39], [40], [41]]. But it was also successfully applied in ecological studies [[42], [43], [44]] with high species identification accuracy based on reference libraries. However, considering the need for accurate species identification in fisheries science described above, it is surprising that the method has so far not been applied to fish eggs.

The main advantages of this method opposing to DNA barcoding are the reduced costs [43] but also the short sample handling times while retaining high identification success. These advantages are particularly useful for a potential application in fish stock assessment, where relatively large numbers of eggs need to be identified and results usually need to be made available for assessment working groups with rather short deadlines. Therefore, the present study intends to test the suitability of MALDI-TOF MS for the identification of fish eggs, using field samples collected in the North Sea that contain a mixture of eggs of different marine fish species. At the same time we aim at comparing different identification strategies and recommending adjustments for identification thresholds of these different methods.